Actions, functions and failures in dynamic
environments
MORTEN LIND
Center for Human-Machine Interaction. Report CHMI-8-2000
1.0 INTRODUCTION
The overall purpose of this report is to analyse relations between action concepts
and concepts of function and failure. The investigation is based on the theory of
action developed by VonWright (1963) and explore the formalized framework
offered by this theory to define the relations between action concepts and concepts
of function and failure. The work reported here is part of the authors research on
formalization of means-end concepts for the analysis of complex industrial
automation systems (see also (Lind, 1994) and (Lind, 2001)). It should be noted
that the work is of preliminary nature and may therefore contain material that is
inconclusive.
2.0 A THEORY OF ACTION
This section introduces the basic ideas of VonWrights theory of action. This theory
is gradually extended in the report in order to accommodate the needs of the
analysis.
2.1 Elementary Changes
The starting point of VonWrights analysis of action is the observation that actions
can be characterized by the change they cause in the environment. A typification of
actions can then be obtained if changes can be typed. If we consider a state of
affairs described by the proposition p, VonWright distinguish between the four
types of elementary changes shown in table 1 where ∼p means that p is not true
and the formula ∼pTp should be read ‘∼p then p’. The four types are the
combinations that are logically possible. It should be noted that the notion of
change implies a notion of time because the formula pTq means that p precedes q
in time. VonWright actually distinguish between two interpretations of the T
namely ”and then” and ”and next” referring to performances and processes
respectively (VonWright, 1965)(VonWright, 1966). These distinctions will not
concern us here. Note also that the state of affairs p or q are generic and may
have a variety of interpretations depending on the nature of the environment and
the aspect considered. In other words the meaning of p depends on how we choose
to characterize state of affairs in the environment. This choice is obviously
dependent on the domain and the problem under investigation. The types of
elementary actions can therefore be used to describe dynamic environments where
multiple representations are required in order to characterize the changes caused
by the interventions of an agent.
2.2 Elementary Actions
To each of the four elementary change types there are corresponding elementary
action types, which can be divided into elementary interventions and elementary
omissions (table 1). The distinction between interventions and omissions is used to
describe actions where the agent decide to influence the environment in order to
change its state into a desired end state (i.e. to intervene), and actions where the
agent decide to be passive i.e. omissions where the natural dynamics of the
environment bring about the desired end state. This means that not doing is
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considered and action if it is intentional. It should however be noted that an action
can only be considered an omission if the agent is capable and has the opportunity
to action. In order to distinguish interventions from omissions, the formula
representing actions need to be extended to the form pT[qIs] as proposed by
VonWright. The formula is read as follows: the environment is initially in state p
and then (T) in state q instead (I) of being in state s. The distinction between an
elementary change and an elementary action is accordingly related to the fact that
the environment would be in state s due to its natural dynamics (or to the
intervention of another agent) instead of the desirable state q if the intervention
was not done. This means that the state q cannot be the same as the state s in
formulae defining the four elementary interventions. Furthermore, in the state of
affairs s and q should be the same in an omission. This is indeed so in table 1.
1
TABLE 1. Elementary changes, interventions and omissions (adapted from VonWright )
Elementary change
Elementary intervention
Elementary omission
∼pTp
p happens
∼pT[pI∼p]
produce p
∼pT[pIp]
let p happen
pTp
p remains
pT[pI∼p]
maintain p
pT[pIp]
let p remain
pT∼p
p disappear
pT[∼pIp]
destroy p
pT[∼pI∼p]
let p disappear
∼pT∼p
p remains absent
∼pT[∼pIp]
suppress p
∼pT[∼pI∼p]
let p be absent
It is this intentional nature of intervention and omissions that is the basis for the
definition of failures introduced later. If the agent had no intentions, changes in
the environment would have no significance i.e. it would not be meaningful to talk
about failures2
In order to explain the nature of the four types of intervention we will assume
that p represents the state ’the valve is open.’ We will first consider ~pT[pI~p]
describing the action of changing a world where ∼p is true into a world where p is
true. Thus ~pT[pI~p] whose generic meaning is ’the production of p’ is in our
example represented by the sentence ’the valve is being opened.’ The expression
pT[~pIp] describes the action ’the destroying of p.’ With the example it describes
the action of closing the valve. The action pT[pI~p] describes that the world does
1
2
The term ’maintain’ is used here for convenience instead of the term ’preserve’ used by
VonWright.
It will be shown later that this is not entirely correct because an agent can fail by expecting
something to be the case, which is in fact not turning out to be true. It is therefore
necessary to distinguish between failure in intention and failure in expectation. The
expectations could be about the future state of the physical environment or be about the
intentions of another agent. The agent could also fail by not being capable of bringing
about the end state se (defeated by the antagonist).
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not change in the feature described by p on two successive occasions, i.e., it means
’the maintenance of p.’ In our example the intervention pT[pI~p] therefore would
describe the action ’keeping the valve open.’ Finally ~pT[~pIp]describes the world
unchanged in the feature described by ~p. This action therefore represent ’the
suppression of p i.e. a situation where the valve is closed but will open unless an
agent does not keep it closed. The valve could be, e.g., a pneumatic valve designed
to open in the event of loss of air. If there is air loss the operator could manually
suppress the opening of the valve by keeping it closed.
2.3 Concurrent Actions
Actions can also be dependent through their conditions such that the following
pairs of actions are concurrently present:
Two agents affecting the same state of affairs (who win?).
(maintain p, destroy p)
(maintain p, let p disappear)
(maintain p, p disappear)
(produce p, suppress p)
(produce p, p remains absent)
(produce p, let p be absent)
(destroy p, p remains)
(destroy p, let p remain)
(suppress p, p happens)
(suppress p, let p happen)
These are related to the counterfactual aspects of intentional actions. These
dependencies, that assume the presence of two agents, mean that the action
maintain p is always present concurrently with destroy p and produce p is
always present together with suppress p. The reason for these constraints on the
combination of the elementary actions is of course that we are only considering a
single state p. Note that an agent may not know whether another agent or mother
nature is responsible for the dynamics of the environment. As an example, the
agent may not know that the destroying of a state p he is trying to maintain is
caused by an agent having the intention to destroy p or he is fighting against the
workings of natural forces3.
The conditions for the actions derived from VonWright’s analysis are important
because they define conditions for the mutual fitness of a set of composite actions
comprising a plan or performance. If a condition is not fulfilled the action cannot
be accomplished. Satisfaction of the conditions therefore ensure a smooth
unbroken flow of activities. The structures obtained by the composition of
elementary actions could therefore called activity flow structures4.
3
4
The natural forces in play may be devised by a design agent that has modified the natural
environment according to his intentions.
There is here a link to the concepts of Multilevel Flow Modeling (MFM) developed by the
present author (Lind, 1994). The analysis of action concepts presented in the present
report is part of a research effort to develop a more general approach to the modeling
problems addressed by MFM. It is expected that MFM can be embedded in a more general
framework where concepts of action (and function) play an essential role.
4
The analysis above does not tell which of the agents that succeed in realizing his
intention. In order to address this question we need to know more than the theory
of action of VonWright can give us. The theory only provides a catalog of the
possible outcomes of the interaction. In order to determine which of the outcomes
that are realized we need to know more about the causal factors involved. This is
the type of problem addressed by theories of dynamics e.g. from the natural
sciences, but the force dynamics of Talmy (1988) from the field of cognitive
semantics should also be mentioned. Talmy’s concept of force is a metaphor to
physical forces and the validity of his theory is therefore questionable when it is
used to describe the interaction between humans and artifacts of even moderate
complexity. Here it is often inappropriate to characterize interactions between
humans and physical artifacts entirely through concepts of force. It would for
example be strange to describe the starting of a motor only in terms of forces. To
describe the dynamics of pressing the start button we obviously require the
concept of force from physics because the operator is interacting with a spring
designed to keep the button either off or on. However, this level of description, that
may be relevant for analyzing problems with the switch, is quite irrelevant to the
intent of the operator, which is to start the motor. Admittedly, it would be possible
to go through an analysis in terms of (physical) forces to follow the causal chain
from the pressing of he button to the acceleration of the motor shaft. But we are in
this way led to descriptions on a too high level of detail. VonWrights analysis does
not suffer from these problems. However, Talmy’s force dynamics may be used to
report on how humans express themselves through natural language about their
experience with the physical world and could in this way contribute to the
engineering of human machine interfaces. However, the serious problem of validity
is still there to be solved in order to avoid misrepresentation of the artifact in the
interface. Misrepresentation is a source of failure because it increases the
complexity of the operator’s task.
2.3.1 Conditions for intervention and antagonists
The four elementary interventions can, as pointed out by VonWright, only be done
provided some conditions are fulfilled. As an example; it is not possible to do the
maintenance of p if p not is and will vanish unless maintained. Thus the action
keeping the valve open is only meaningful if the valve is already open and the
valve will close if the action is not done. These conditions are of a logical nature as
they are intrinsic to the definition of an intervention i.e. through the meaning of
the terms si, se and sh in the formula siT[seIsh] and through the constraints
that are imposed on these terms. Thus the unequality of se and sh implies that
the intervening agent is counteracted by nature or by other agents in the
environment. The concept of an intervention therefore implies the notion of a
antagonist i.e. some agency or disposition of the environment that may hinder the
agent in bringing about the state se. However, according to the present definition
of an intervention, the antagonist is always defeated i.e. fail because the agent
obtain the intended end state of affairs. The nature of the counteraction depends
on the type of intervention. Correspondences between interventions, conditions
and the (defeated) antagonists are shown in the table below.
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TABLE 2. Elementary interventions and types of antagonists
Elementary intervention
Condition for intervention
Type of
antagonist
produce p
p is not and will remain absent
unless produced
suppressor
(suppress p)
maintain p
p is and will disappear unless
maintained
destroyer
(destroy p)
destroy p
p is and will remain unless
destroyed
maintainer
(maintain p)
suppress p
p is not and will happen unless
suppressed
producer
(produce p)
2.3.2 Conditions for omission and substitutes
As the four elementary omissions describe actions where the natural dynamics
(disposition) of the environment by itself or by the intervention of another agent
bring about the desired end state, there is no difference between the states q(se)
and s(sh)in Table 1. There is then clearly a distinction between interventions and
omissions. However, the difference between a mere change and an omission is not
completely clarified. The difference can only be expressed if the belief or
expectations behind the agent decision not to act is introduced in some way in the
formulae. The concept of an omission implies the notion of a proxy because the
dynamics of the environment bring about the state that the agent intended. The
change is caused by mother nature or by another agency that substitute the agent.
The substitute bring about the intended state instead of the agent. Note that a
substitute should not be considered as a helper since this would imply concurrent
intervention by the agent and that the agent was failing when trying to bring
about the state intended. Failures (and helpers) will be discussed later.
The conditions for omission are expressed in the formula siT[seIsh] through the
equality of se and sh meaning that the end state intended is the state that will
occur if the agent was not interacting with the environment.
An omission then imply a decision not to act grounded in the belief that the
environment will bring about the desired state or that an agent in the environment
have the intention to produce or maintain it. The formula does not express these
beliefs in its present form and extensions are required in order to characterize
certain types of failure. These extensions are introduced later.
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TABLE 3. Elementary omissions and types of substitute
Elementary omission
Condition for omission
Type of substitute
let p happen
p is not and will happen
producer
(produce p)
let p remain
p is and will remain
maintainer
(maintain p)
let p disappear
p is and will disappear
destroyer
(destroy p)
let p be absent
p is not and will remain absent
suppressor
(suppress p)
2.4 A Possible Reduction
The eight elementary actions may be reduced to four by using the following
equivalences:
produce ∼p
maintain ∼p
destroy ∼p
suppress ∼p
let ∼p happen
let ∼p remain
let ∼p disappear
let ∼p be absent
⇔
⇔
⇔
⇔
⇔
⇔
⇔
⇔
destroy p
suppress p
produce p
maintain p
let p disappear
let p be absent
let p happen
let p remain
These equivalences give a certain freedom of expression. They may be useful in
modeling situations of conflict, e.g., where a state of affairs p is maintained by one
agent and another agent is suppressing p. Logically the same situation could also
be described as a situation where the second agent is maintaining ∼p. In the latter
case the description of the situation would include both p and ∼p and it would not
be immediately obvious from the description that the agents are in conflict. The
existence of a conflict would also depend on whether both p and ∼p can be true at
the same time. This is not possible in binary valued logic but is perfectly possible
in multi-valued logics or in fuzzy logic that allows degrees of truth. A reduction of
the four action types to two as shown in Table 4, seems on these grounds to be
problematic5.
5
A firm conclusion on this point is not attempted at the moment as more analysis of the
problem is required. The analysis of failure types later in the paper take advantage of the
reduction and may therefore later turn out to be incomplete.
7
TABLE 4. Elementary changes, interventions and omissions (reduced)
Elementary changes
Elementary intervention
Elementary omission
∼pTp
p happens
∼pT[pI∼p]
produce p
∼pT[pIp]
let p happen
pTp
p remains
pT[pI∼p]
maintain p
pT[pIp]
Let p remain
2.5 Two Agents
VonWright extend the analysis of actions to include also the description of
interaction between two or more agents. The description of an interaction requires
a deal more state descriptions in order to properly define the intentionality. We
need to know the following when we have two agents A and B interacting:
si : the intial state of affairs
sAB : the actual subsequent end-state of affairs with the two agents in it
sh : the (hypothetical) end state of affairs had there been no agent at all
sA : the (hypothetical) end-state of affairs obtained had A been alone
sB : the (hypothetical) end-state of affairs obtained had B been alone
Four situations can be distinguished as shown in Table 5.
TABLE 5. Four situations with none, one and two agents
Agents
Formula
None
siTsh
Explanation
Illustration
sh
The environment changes state
from si to sh by its own
dynamics.
si
sh
siT[sAIsh]
A
si
The agent A intervene and the
state of the environment changes
from si to sA instead of sh
sA
A
sh
B
A and B
siT[sBIsh]
siT[sABIsh]
si
The agent B intervene and the
state of the environment changes
from si to sB instead of sh
Both agents A and B intervene
and the state of the environment
changes from si to sAB instead of
sh
sB
B
sh
si
A
sAB
B
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The formula introduced earlier describing the actions of a single agent siT[seIsh]
is here extended in order to include the hypothetical states sA and sB to the
following formula siT[sABIsh|sA,sB].We get then the elementary situations
shown in Table 6.
TABLE 6. The elementary situations with two agents.
A alone: siT[sAIsh]
(A and B): siT[sABIsh]
Interventions
produce p
maintain p
destroy p
suppress p
∼pT[pI∼p]
∼pT[pI∼p]
B let A produce p
∼pT[∼pI∼p]
B prevents A from
producing p *
pT[pI∼p]
B let A maintain p
pT[∼pI∼p]
B prevents A from
maintaining p *
pT[∼pIp]
B let A destroy p
pT[pIp]
B prevents A from
destroying p *
∼pT[∼pIp]
B let A suppress p
∼pT[pIp]
B prevents A from
suppressing p *
∼pT[pIp]
B let A let p happen
∼pT[∼pIp]
B prevents A from
letting p happen *
pT[pIp]
B let A let p remain
pT[∼pIp]
B prevents A from
letting p remain *
pT[∼pI∼p]
B let A let p disappear
pT[pI∼p]
B prevents A from
letting p disappear *
pT[∼pI∼p]
B let A let p be absent
pT[pI∼p]
B prevents A from
letting p be absent *
pT[pI∼p]
pT[∼pIp]
∼pT[∼pIp]
Omissions
let p happen
let p remain
let p disappear
let p be absent
∼pT[pIp]
pT[pIp]
pT[∼pI∼p]
pT[∼pI∼p]
It should be noted that all cases above marked with ”*” are changes where A fail
due to the intervention of B. A fails because either because B has a conflicting
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interest or because the consequences of B’s action prevents A from succeeding
(influences the opportunities or capability for action).
Examples:
A and B:(p&q)T[(~p&~q)I(p&q)|(~p&q),(p&~q)]
A alone:pT[~pIp]
B alone:qT[~qIq]
A destroys p and let B destroy q
B destroys q and let A destroy p
These two descriptions represent two perspectives on the same situation 1) B is a
substitute and alternatively 2) A is a substitute.
A and B:(p&q)T[(~p&q)I(p&q)|(~p&q),(p&~q)]
A alone:pT[~pIp]
B alone:qT[~qIq]
A destroys p and prevents B from destroying q
B let q remain and let A destroy p
Note that A cannot distinguish between the vanishing of q due to the intervention
by B and the disappearance of q due to natural causes.
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2.6 Examples
In order to illustrate the use of the action types developed above we will consider
the manipulation of a physical object in space. The examples have a general
interest because the dynamics of physical domains are described by so-called state
spaces. These spaces are abstract but are usually explained and represented in
terms of a physical space metaphor. In state spaces a change, and accordingly also
an action, is defined by the transition between two locations. The examples are
obviously also relevant for other domains where the space metaphor can be used.
6
TABLE 7. Example1: Translocation of an object
Intervention
move-to(x,y)
Omission
?
? let-move-to(x,y)
y
?
y
The object y move by itself to
location x
The object y is moved to location x
x
x
let-stay-at(x,y)
keep-at(x,y)
x
The object y is kept y at location x.
x
The object y stay by itself at
location x
y
y
?
move-from(x,y)
? let-move-from(x,y)
The object y is moved away from
location x
keep-away-from(x,y)
The object y is kept away from
location x
y
?
The object y move by itself away
from location x
.
x
let-stay-away-from(x,y)
y
x
?
The object y stay away by itself
from location x
?
y
?
x
y
x
?
Note that the eight types of action in Table 7 implicitly assume two roles, a spatial
location and a movable object. Most actions include additional roles for their
definition. The roles define opportunities for objects and agents. The fulfillment of
a role may be conditional on a state of affairs (see also Lind, 2001).
6
Full lines show the result of an intervention. Dotted lines show natural dynamics of the
object
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TABLE 8. Example 2: Putting in and getting out an object from an enclosed space.
Intervention
put-in(x,y)
Omission
let-get-in(x,y)
y
The object y is put into x
The object y is put into x by itself
keep-in(x,y)
let-stay-in(x,y)
The object y is kept in x
y
get-out(x,y)
The object y is kept out of x
The object y stay inside x by itself
y
let-get-out(x,y)
The object y is taken out of x
keep-out(x,y)
y
y
y
The object y get out of x by itself
.
let-stay-out(x,y)
y
y
The object y stay out of x by itself
Note, as above, that the eight types of action in Table 8 implicitly assumes the
introduction of two roles, here a container and a contained-object.
2.7 Sequences of Elementary Actions
The elementary actions can be combined into sequences. However, due to strong
logical relations between the elementary actions the number of possible sequences
is restrained. The number is extremely limited because each action has a
condition to be satisfied and because that condition should be the result of the
preceding action in the sequence. This can be derived from the so-called ‘praxis
triangle’ shown above. Since we have eight possible actions according to
VonWrights theory we can expand and translate the triangle into the graph shown
below (each arc label corresponds to the top of a triangle). It is seen that the
possible sequences may include both interventions and omissions.
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produce p
(~p)
let p happen
(p)
let p be absent
(~p)
suppress p
(p)
~p
p
let p rem ain
(p)
m aintain p
(~p)
let p disappear
(~p)
destroy p
(p)
FIGURE 1. State transformations created by the elementary actions.
The following two examples demonstrate the combination of elementary actions
into sequences.
~p
A
A
produce p
p
m aintain p
p
let p rem ain
A
p = ’location of A is x’
move-to
keep-at
~p
A
A
A
table
table
move-to
produce p
p = ’location of A is x’
let-stay-at
FIGURE 2. Example sequences of elementary actions from the blocks world.
2.8 Contradictory and antonymic states
Transitions between states are in VonWrights formulation contradictory. However
states can also be defined as alternative antonymic states. Thus a transition
between a states p and q will be described by the formula
pTq
13
which is equivalent to
(p&~q)T(~p&q)
2.9 State Spaces
State spaces can be constructed by composing atomic states. There may be states
that cannot be obtained at the same time or that are logically related. States may
also be decomposed into state descriptions on a more fine grained level.
Note that state and action descriptions are interchangeable. Thus, omissions
where an agent let the environment maintain (or suppress) a state can also be
described as a state of the environment. Consider the blocks world example where
a put-down action (an intervention) is followed by a let-stay action (an omission).
However, the omission let-stay is equivalent to the state on-table. The choice of
description depends on the point of view or focus. If we describe the situation in
state terms we focus on the block whereas an action description would focus on the
agent.
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3 INTERPRETATIONS
The definition of action types presented above was based on four so-called
elementary changes, which were distinguished exclusively on the basis of logical
form. Further distinctions are possible and necessary for describing interactions in
complex systems. The action types have many interpretations depending how
states are defined i.e. the semantics of the terms that enter into the proposition p.
Any statement of a proposition must contain words for terms and at least for one
relation (Langer(1953): a logical picture of a state of affairs). Depending of the
meaning of the terms and the relation various types of states can be defined. For
each type of state a set of corresponding elementary actions (and changes) can be
defined.
3.1 Types of Change
The distinction between changes that are caused by an action and a change in the
action itself is important. Watzlawick (1974) distinguish between first and second
order changes. By a change in the action we mean for example the disappearance
of an opportunity to action. The disappearance of the opportunity may be due to an
intervention, or to the omission of an agent intentionally letting the opportunity
disappear. As another example of changes in the action we could mention a change
in its state of performance. These distinctions are of fundamental importance for
the understanding of the functional organization of complex artifacts like
industrial production plants and play a vital role in e.g. diagnosis of malfunction
and planning of control actions.
It is obvious that a logic of changes in the action can be described within the
framework of VonWrights analysis of elementary actions. However, an application
of the analysis require a detailed analysis of what we actually mean by ’state of
affairs’, a notion that is left unexplored by VonWright.
3.2 State of Affairs
This subject is a complex one. However, the few selected distinctions discussed
below illustrate the possibility of a variety of state types.
3.2.1 States of being
existence (p = x exist: x is an object)
produce ’x exist’(provide x)
maintain ’x exist’(conserve x)
destroy ’x exist’(eliminate x)
suppress ’x exist’
let ’x exist’ happen
let ’x exist’ remain
let ’x exist’ disappear
let ’x exist’ be absent
presence (p = x is at s: s is a location in space)
produce ‘x is at s’
maintain ‘x is at s’
destroy ‘x is at s’
suppress ‘x is at s’
15
let
let
let
let
‘x
‘x
‘x
‘x
is
is
is
is
at
at
at
at
s’
s’
s’
s’
appearance (p =
happen
remain
disappear
be absent
x appears at t: t is a point in time)
produce ’x appears at t’
maintain ’x appears at t’
3.2.2 States of action
doing (p = x is done by a: x an action, a an agent)
produce ’x is done by a’(initiate)
maintain ’x is done’ (perform)
destroy ’x is done’ (terminate)
suppress ’x is done’(inhibit)
let ’x is done’ happen
let ’x is done’ remain
let ’x is done’ disappear
let ’x is done’ be absent
capability (p = ’a is capable of x’: a an agent, x an action)
produce ’x can be done by a’ (enable))
maintain ’x can be done by a’ (ensure)
destroy ’x can be done by a’ (disable)
suppress ’x can be done by a’ (impede)
let ’x can be done by a’ happen
let ’x can be done by a’ remain
let ’x ca be done by a’ disappear
let ’x can be done by a ’ be absent
opportunity(p =’x is opportune for a’:a an agent, x an action)
produce ’x is opportune for a´
maintain ’x is opportune for a’
destroy ’x is opportune for a’
suppress ’x is opportune for a’
let ’x is opportune for a’ happen
let ’x is opportune for a’ remain
let ’x is opportune for a’ disappear
let ’x is opportune for a’ be absent
The distinctions between the states of capability ’x can be done by a’ and
opportunity ’x is opportune for a’ and the state ´x is done’ are
important because the two former states provide the necessary conditions for the
latter (the doing). Note that the conditions are not sufficient. The decision to act
and the initiation of the action are missing. These logical relations are crucial for
the ordering of actions into activity sequences. The distinctions can actually
account for the overall logic structure of e.g. start-up plans of industrial process
plants.
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4.0 MULTIPLE DESCRIPTIONS
The results of the analysis of action types are generic since we have not given the
state of affairs p a specific interpretation. The interpretation can be chosen in each
particular case depending on the problem. Multiple description of an activity can
be obtained in his way. Descriptions may be organized in various ways. One
interesting possibility is to order descriptions in means-end structures.
In ship operation we can use the categories on several task levels. A description
of ship operations on several task levels is shown in Table 9. It is seen that the
ship can be described on the levels of actuation, maneuvering, track following and
navigation. The levels are distinguished by the goals to be obtained, the
disturbances to be counteracted and by the time horizon. The world model on each
level can be used to propose plans (sequences of actions). The goal to be obtained is
defined in terms of the level above.
TABLE 9.The elementary actions applied on ship operations (tentative).
Action type
move-to
Actuation
Obtain rudder
angle or propeller
speed.
Task
Maneuvering
Tracking
Obtain given
Reach given track
position, course or
speed.
stay-at
Keep rudder angle
or propeller speed.
Keep position,
speed or course.
Keep on track
Stay at landmark
move-from
Change from
actual rudder
angle or propeller
speed.
Avoid rudder
angle or propeller
speed.
Change from
actual position,
speed or course.
Leave actual track
Move from
landmark
Avoid position,
speed or course.
Avoid track
Avoid landmarks
and obstacles.
Drifting to desired
position, speed or
course.
Move to desired
track by
maneuvering or
drifting.*
Move to desired
landmark by
tracking or
drifting.*
stay-away-from
let-move-to
Drifting to desired
rudder angle or
propeller speed.
let-stay-at
Drifting on desired Drifting on desired Keep at track by
rudder angle or
position, speed or
maneuvering or
propeller speed.
course.
drifting*
let-move-from
Drifting away
from actual rudder
angle or propeller
speed.
let-stay-away-from Keep away from
rudder angle or
propeller speed by
drifting.
Navigation
Reach landmark
Keep on landmark
by tracking or
drifting*
Drifting away
from actual
position, speed or
course.
Move from track
Move from
by maneuvering or landmark by
drifting*
tracking or
drifting*
Keep away from
position, speed or
course by drifting.
Keep away from
Keep away from
track by drifting or landmark by
maneuvering.*
drifting or
tracking
navigating.*
Drifting means here to let the system behave according to its own dynamics (which
may involve the dynamics of the underlying levels of control).
17
5.0 FUNCTIONS
5.1 Functions and Indirect Agency
When an agent intervenes in a dynamic environment we talk about direct agency.
When a designer create and object with the intention to let the object perform a
function under suitable conditions we talk about indirect agency. Concepts of
action and function are therefore closely related. But functional concepts include
both passive and active meanings. In the passive meaning we refer to entities that
are objects of change (i.e. that let the changes happen to them). In the active
meaning (implying the concept of indirect agency) we refer to objects that change
the state of other objects. The functions of these objects are defined by the state
transformation i.e. the action type.
5.2 Functions and Omissions
Omissions play also an important role in understanding the concept of function.
Consider the operation of an electronic switch. The switch is turned on by an
operator by flipping the lever. By flipping the lever the operator intervenes in the
environment. After flipping the lever the switch stays in the new position and the
operator omit further action expecting that the spring in the switch to maintain
the lever position. This expectation has a threefold justification: 1) the spring is
actually capable of maintaining the switch position and 2) the spring has the
opportunity to do it i.e. the operator has flipped the lever to the position where the
spring can keep it in position and 3) the spring does it i.e. it has the proper
disposition or tendency to exert force that will keep the lever in position. The
expectation may be justified by the (social) fact that (design) function of the spring
is ‘to maintain lever position’. These expectations may be shared by several agents.
It is realized that functions are ascribed to objects in the environment in situations
where the agent omit to act (let the environment do the work). Consider also the
examples in Figure2. In this case we can say that the table has the function of
keeping the block in a certain vertical position. This is actually the way the table is
used (use function). This explains also that the gripper can release the block and
omit further action. When omitting to grip the block the task of keeping the block
in the vertical position is allocated to the table.
18
6.0 FAILURES
The aspects of action and the distinction between capability and opportunity
introduced earlier can be used to explore the ways an action can fail. For a start
we can distinguish between two overall categories of failure, one relating to the
possibility for action and the other to the performance of the action. Thus an action
can fail because the agent had an intention to act, but did not posses the capability
to do it or the environment did not offer the opportunity for action. In addition the
realization of the intention i.e. the performance of the action can still fail in any of
the aspects mentioned by Lind(2001) even though the required capability and
opportunity is available. Thus an action can fail by being done by the wrong agent
(WHO). It can fail in the result obtained (WHAT). It can fail in the manner it was
done or by not using the proper means (HOW). An action can also fail by being
done at the wrong point time, in a wrong place or under wrong circumstances
(CONTEXT). Finally an action can fail by being initiated by a wrong cause, by
being done with the wrong aim or in an improper state of mind (WHY). These
types of performance failure may be relevant in different contexts.
6.1 Failure Types
Action failures can be accordingly be categorized into three fundamental types as
illustrated below. In the figures, s represent the actual state, G the set of goal
states and O the set of possible states that can be obtained in the given
environment - the opportunities. C are the states that the agent is capable of
obtaining. The intersection R of O and C define all the states that can be reached
by the agent. R is therefore called the reachability set. This distinction between
capabilities and opportunities actually presupposes a separation of the agent and
the environment by a boundary of interaction (see also Lind (2001)).
We can refine our analysis of action failure types by introducing the set of goal
states G. G is the set of states that are the intended consequences of the agent’s
action. The resulting failure types are shown in Table 10.
TABLE 10. Failure types
Failure in performance
The agent has the opportunity
the capability to obtain all
states in G but fail because
actual state s obtained does
belong to the goal set G.
and
goal
the
not
R
G⊂O∩C
s
G
O
C
s∉G
Failure in opportunity
There is misfit between the goal set
of the agent and the opportunities
offered by the environment. The
agent is capable of obtaining all
states in G but the opportunities are
not available.
.
R
s
O
G
C
G⊂C/O
s∉G
19
Failure in capability
There is a misfit between the agents
capabilities and intentions. The
opportunities are there to obtain the
states in G but they cannot be
reached because the agent is not
capable.
G ⊂ O /C
s∉G
s
G
O
R
C
6.2 Interpretations
The analysis of failure types presented above can be expanded tentatively in
several directions by imposing different interpretations on the state of affairs s.
The following distinctions can be proposed if s is interpreted as action aspects i.e.
performance, modality, and circumstances representing features of an action
(Lind, 2001).
TABLE 11. Failure types and aspects of an action
Aspect
Performance
Modality
Interpretation
O is the set of results that are given opportunity, G is the set of results
aimed at, C is the set of results that is within the capability of the
agent and s is the result obtained.
manner
means
Circumstance
timing
location
O is the set of manners that are given opportunity, G is the set of
intended manners and C is the set of manners that is within the
capability of the agent
O is the set means that are given opportunity (available), G is the set of
intended means and C is the set of means that the agent is capable of
using
O is the set of times that are given opportunity, G is the set of intended
times for action and C is the set of times that the agent is capable of
realizing
O is the set of locations that are given opportunity, G is the set of
intended locations and C is the set of locations that the agent is capable
of using
6.2.1 An Example: Acts of communication
Considering acts of communication such as sending and receiving a message we
can in this way define a variety of failure types of communication acts:
TABLE 12. Failures in sending a message.
Aspect
performance
modality
manner
Interpretation
O is the set of messages that can be received by the environment
G is the set of messages that should be sent
C is the set of messages that the agent is capable of sending
s is the actual message sent
O is the set of manners of receiving messages that are given
opportunity
20
means
circumstance
timing
location
G is the set of manners of sending messages that are intended
C is the set of manners of sending messages that is within the
capability of the agent
O is the set means for sending messages that are given opportunity
(available)
G is the set of intended means of sending messages
C is the set of means of message sending that the agent is capable of
using
O is the set of times for sending messages that are given opportunity
G is the set of intended times for sending messages
C is the set of times that the agent is capable of sending messages
O is the set of location for sending messages that are given opportunity
G is the set of intended locations for sending messages
C is the set of locations for sending messages that the agent is capable
of using
TABLE 13. Failures in receiving a message.
Aspect
performance
modality
Interpretation
O is the set of messages that can be sent by the environment
G is the set of messages that should be received
C is the set of messages that the agent is capable of receiving
s is the actual message received
manner
means
circumstance
timing
location
O is the set of manners of sending messages that are given opportunity
G is the set of manners of receiving messages that are intended
C is the set of manners of receiving messages that is within the
capability of the agent
O is the set means for receiving messages that are given opportunity
(available)
G is the set of intended means of receiving messages
C is the set of means of message reception that the agent is capable of
using
O is the set of times for receiving messages that are given opportunity
G is the set of intended times for receiving messages
C is the set of times that the agent is capable of receiving messages
O is the set of location for receiving messages that are given
opportunity
G is the set of intended locations for receiving messages
C is the set of locations for receiving messages that the agent is capable
of using
21
5.3 Failures of Performance
The changes of state caused by an agent interacting with a dynamic environment
are not always successful. Sometimes the action fails because it is not producing
the result intended by the agent. In other situations an agent can decide not to
intervene with the environment because he expects that the state of the
environment will change into a desirable end state by its own dynamics. However,
such an omission can also be considered a failure when the resulting state of
environment did not turn out according to expectations. The evaluation of actions
in dynamic environments is accordingly not a simple task. The need to consider
differences in the states obtained in the environment increases the complexity of
the task. Thus, an intervention where the agent counteract the natural dynamics
of the environment so that its state is maintained, is quite different from an
intervention that produces a new state. These problems will be approached in the
following by the derivation of a set of elementary types of successes and failures.
In the formula siT[seIsh] used above to define actions it is not possible to
distinguish a successful intervention from one that has failed. Also we cannot
define what is to be understood by omission failure. When omitting to act the
agent is taking advantage of the natural dynamics of the environment to bring
about the desired end state. The agent must therefore expect that the state will be
obtained and this belief must be based on some model of the environment. These
problems arise because VonWright’s analysis do not make sufficient distinctions. It
has a basic limitation because the action always result in the desired end state i.e.
that the actual state obtained se is the state intended. We need therefore to extend
VonWrights analysis with this distinction. By introducing the expectations of the
agent in the formula we will also be able to distinguish between success and
failures of omissions. But since an agent intervene because of an intention to bring
about a state in the environment it must also be assumed that the agent at the
same time also has the expectation that the state will be obtained. If the agent act
but does not expect to realize his intentions he is not rational. This means that in
an intervention, the expected and the intended state must be the same. By
introducing the state expected by the agent we can solve the problems with
failures of omissions and intervention.
We can accordingly summarize the extended problem formulation in the
following way: We have an agent acting in a dynamic environment. The initial
state of the environment is si, the actual state after the intervention is sa instead
of sh that would happen if the agent did not act. The agent has the expectation
that the state after the change would be se (the result intended) This can be
expressed in the modified formulae siT[sAEseIsh].
A successful intervention can then be expressed by the formula siT[pEpIsh] i.e.
the state of the environment after the change was p as expected by the agent. A
failed action has the form siT[pEqIsh] where p and q are not the same states.
The agent failed since the state q was expected instead of sh but p happened. The
intervention failed either because the agent was unable to bring about q or
because his model of the environment was incorrect.
A successful omission be expressed by the formula siT[pEpIp] i.e. the state p
expected to obtain is the same as the state after the change (obtained without
intervention). A failed omission would be expressed by siT[pEqIp] i.e. the state q
22
expected to obtain is not the same as the state p after the change (obtained
without intervention).
TABLE 14.Successes and failures of elementary interventions and omissions.
Elementary intervention
Elementary omission
∼pT[pEpI∼p]
produce p
∼pT[pEpIp]
let p happen
pT[pEpI∼p]
maintain p
pT[pEpIp]
let p remain
pT[∼pE∼pIp]
destroy p
pT[∼pE∼pI∼p]
let p disappear
∼pT[∼pE∼pIp]
suppress p
∼pT[∼pE∼pI∼p]
let p be absent
∼pT[∼pEpI∼p]
failing to produce p
∼pT[∼pEpI∼p]
failing to let p happen
pT[∼pEpI∼p]
failing to maintain p
pT[∼pEpI∼p]
failing to let p remain
pT[pE∼pIp]
failing to destroy p
pT[pE∼pIp]
failing to let p disappear
∼pT[pE∼pIp]
failing to suppress p
∼pT[pE∼pIp]
failing to let p be absent
Success
Failure
Note that in all failed interventions the expected state is complement to the state
that actually is brought about i.e. we have the patterns ~pEp or pE~p in the action
formula. In all failed omissions the state expected by the agent after the change is
the same as the state that would obtain if the action were not done.
5.4 Turning a Failure Into a Success
An agent can turn a failure into a success by revising his expectations. In
retrospect the agent may realize that his expectations were not fulfilled and
change his mind to accept the new situation. Note that the failures are then
changed into successful omissions.
TABLE 15. Failures turned into successes by revision of expectations.
∼pT[∼pEpI∼p]
failing to produce p
pT[∼pEpI∼p]
failing to maintain p
=>
=>
∼pT[∼pE∼pI∼p]
let p be absent
pT[∼pE∼pI∼p]
let p disappear
23
pT[pE∼pIp]
failing to destroy p
=>
pT[pEpIp]
let p remain
∼pT[pE∼pIp]
failing to suppress p
=>
∼pT[pEpIp]
let p happen
∼pT[∼pEpI∼p]
failing to let p happen
=>
∼pT[∼pE∼pI∼p]
let p be absent
pT[∼pEpI∼p]
failing to let p remain
=>
pT[∼pE∼pI∼p]
let p disappear
pT[pE∼pIp]
failing to let p disappear
=>
pT[pEpIp]
let p remain
∼pT[pE∼pIp]
failing to let p be absent
=>
∼pT[pEpIp]
let p happen
5.5 Help as Failure Avoidance
An agent B can sometimes intervene in a situation with the intention of
preventing another agent A from failing. In such situations we can say that the
agent B help the agent A. Different types of help can be derived systematically
from the failure types in Table 14. The result is shown in Table 16.
TABLE 16. Types of help.
A alone: siT[sAIsh]
(A and B): siT[sABIsh]
Interventions
failing
to
produce p
failing
to
maintain p
failing
to
destroy p
failing
to
suppress p
∼pT[∼pEpI∼p]
∼pT[∼pEpI∼p]
∼pT[pEpI∼p]
pT[∼pEpI∼p]
pT[∼pEpI∼p]
pT[pEpI∼p]
pT[pE∼pIp]
pT[pE∼pIp]
pT[∼pE∼pIp]
∼pT[pE∼pIp]
∼pT[pE∼pIp]
∼pT[∼pE∼pIp]
B let A fail
to produce p
B help A to produce p
B let A fail to
maintain p
B help A to maintain p
B let A fail
to destroy p
B help A to destroy p
B let A fail
to suppress p
B help A to suppres p
Omissions
failing
to
let p happen
failing
to
∼pT[∼pEpI∼p]
pT[∼pEpI∼p]
∼pT[∼pEpI∼p]
B let A fail to let p
happen
∼pT[pEpI∼p]
B help A to let p
happen
pT[∼pEpI∼p]
B let A fail to let p
remain
24
let p remain
failing
to
let p disappear
failing
to
let p be absent
pT[pEpI∼p]
B help A to let p
remain
pT[pE∼pIp]
B let A fail to let p
disappear
pT[pE∼pIp]
pT[∼pE∼pIp]
∼pT[pE∼pIp]
∼pT[pE∼pIp]
∼pT[∼pE∼pIp]
B help A to let p
disappear
B let A fail to let p
be absent
B help A to let p be
absent
Note that control actions can be seen as means of helping the designer to realize
his intentions in an uncertain world. There is a direct mapping between action
types and types of control action as shown below (see also Lind, 1994). However,
control actions cannot be defined exclusively as instances of VonWright’s action
types, it is also necessary to include acts of observation, decision and intervention
i.e. the means of control. Otherwise it is not possible to distinguish between
ordinary help and the kind of help provided by control agents.
TABLE 17. Mapping between elementary action and elementary control actions.
Elementary action
Elementary control action
produce
steer
maintain
regulate
destroy
trip
suppress
interlock
6.0 REFERENCES
Langer, S. K. (1953). An Introduction to Symbolic Logic. New York:Dover
Publications.
Lind, M. (1994). Modeling Goals and Functions of Industrial Plant. Applied
Artificial Intelligence, Vol 7.
Lind, M. (2001). Possibilties for Action. Report from Center of Human Machine
Interaction CHMI-7-2000.
Talmy, L. (1988). Force Dynamics in Language and Cognition. Cognitive Science,
vol 12, 49-100.
Watzlawick, P. (1974). Change - Principles of Problem Formation and Problem
Resolution. New York: W. W. Norton & Company.
VonWright, G. H. (1963). Norm and Action. London: Routledge & Kegan Paul.
VonWright, G. H. (1965). ”And Next”. Acta Philosophica Fennica, 18, pp. 293-304.
VonWright, G. H. (1966). ”And Then”. Commentationes Physico-Mathematicae, Vol.
32, Nr. 7, pp.1-11.
25