towards a context-sensitive structure for behavioural rules (context, scope, antecedents, and...

Towards a Context-Sensitive Structure for Behavioural Rules, Bruce Edmonds, Informal Workshop on Qual. Evidence & Rules, MMU, Sept. 2012, slide 1

Towards a Context-Sensitive Structure for Behavioural Rules

(Context, Scope, Antecedents, and Results)

Bruce Edmonds

Centre for Policy Modelling,Manchester Metropolitan University


Summary of Talk: a view from Cognitive Science

Suggest dividing behavioural rules into 4 bits:– Context– Scope– Antecedents– Results

• Since this, I argue, seems to align with human cognitive structure

• Which are each dealt with and updated in different ways (making their use feasible)

• And thus might be a more “natural” structure for human behavioural rules


Different Aspects I


Different Aspects II

Universe of Knowledge

Knowledge indicated by current cognitive context

Knowledge that is possible to apply given circumstances

Cause1 & Cause2… Result1 & Result2…

Cause3 & Cause2… Result5 & Result2…


ContextBit 1:


A (simplistic) illustration of context from the point of view of an actor


Situational Context

• The situation in which an event takes place• This is indefinitely extensive, it could include

anything relevant or coincident• The time and place specify it, but relevant

details might not be retrievable from this• It is almost universal to abstract to what is

relevant about these to a recognised type when communicating about this

• Thus the question “What was the context?” often effectively means “What about the situation do I need to know to understand?


Cognitive Context (CC)

• Many aspects of human cognition are context-dependent, including: memory, visual perception, choice making, reasoning, emotion, and language

• The brain somehow deals with situational context effectively, abstracting kinds of situations so relevant information can be easily and preferentially accessed

• The relevant correlate of the situational context will be called the cognitive context

• It is not known how the brain does this, and probably does this in a rich and complex way that might prevent easy labeling/reification of contexts


The Context Heuristic

• The kind of situation is recognised in a rich, fuzzy, complex and unconscious manner

• Knowledge, habits, norms etc. are learnt for that kind of situation and are retrieved for it

• Reasoning, learning, interaction happens with respect to the recognised kind of situation

• Context allows for the world to be dealt with by type of situation, and hence makes reasoning/learning etc. feasible

• It is a fallible heuristic with social roots in terms of the coordination of action, norms, habits


Some Possible Examples of Cognitive Context?

• Greeting someone you do not know• A lecture• An interview• Being Lost• Being Socially Embarrassed• Travelling on a train/bus• Leaving home to go somewhere• Accidently bumping into someone you do

not know on the pavement/in the corridor


Some Research Responses to Context-Dependency

A number of responses:• Only do research within a single context,

resisting any generalisation • Only use discursive, natural language

approaches where context is implicitly dealt with (but also mostly hidden)

• Try to see what (inevitably weaker knowledge) is general across the various contexts in what is being studied


Context-Dependency and Randomness

Lots of information lost if randomness used to “model” contextual variation


However

• Although Cognitive Context in General might be hard to identify

• Socially Entrenched Contexts are often rather obvious

• But one needs to drop the imperative of looking (only) for abstract and general theories for behaviour

• Being satisfied with more “mundane” and context-dependent accounts


Choice and Update of Cognitive Context

• CC is largely learnt from experienced situations in a rich and unconscious way

• Occasionally one can realise one has the wrong context if a lot of the detailed knowledge it indicates is simultaneously wrong but which is the right CC is a matter of recognition from past positive learning

• Once CC is learnt it is very difficult to change, but new CC can still be learnt


Identifying Context from Narrative Evidence

• Apart from socially entrenched contexts (lectures, parties, interviews etc.)…

• …the relevant CC is hard to identify from narrative evidence because:– To a large extent, we recognise the right CC for any

text unconsciously and easily– The CC are learnt in a rich, “fuzzy” manner over a

long period of time by inhabiting them which resists reification

• This is one of the prime needs: how to “mark up” the CC behind narrative evidence?


ScopeBit 2:


About Scope

• By “scope” I mean the reasoning as to which knowledge is possible given the circumstances

• For example, if all the seats are taken in a lecture, then the norms, habits and patterns as to where one sits do not apply

• Reasoning about scope can be complex and is done consciously

• However once judgements about scope are made then they tend to be assumed, unless the situation changes critically


Scope vs. Cognitive Context

• Both scope and cognitive context determine which knowledge is useful for any particular situation that is encountered

• However, they play very different roles:– CC is learnt using pattern recognition over a long

time, but then is largely a ‘given’, is almost impossible to change when learnt, is quick and automatic and is socially rooted

– Scope is largely reasoned afresh each time, taking effort to do so, is possible to re-evaluate but only if needed, and is more individually oriented


Identifying and modelling scope

• Compared to CC, scope is relatively well studied using formal models of reasoning– e.g. Updating Markoff/state representations of

causation, non-monotonic logics, causation in Baysian networks etc.

• Scope plays a relatively explicit part in human language, sometimes being explicitly stated, at other times using relatively well understood rules – e.g. conversational implicature

• It is often possible to infer participant’s judgements as to scope and possibility, when not explicitly mentioned


(local) Narrative StepsBits 3&4:


Encoding Narrative Steps

• *If* CC and scope is identified then, I hypothesize, the local narrative structure will be easier to understand, because changing CC and/or scope can do a lot of the “work” in expressing/encoding knowledge

• Within CC & scope I suggest a simple basic structure of sets of statements of the form:

(on the whole) Z follows/followed from A, B…• A very special case of this is when we say that: A,

B… implies Z or that: A, B… causes Z • (I will write A, B…Z), where A, B are the

“Antecedents” and Z is the Results


About Narrative Steps

• These might not be crisp but of the nature More A and B tends to result in more Z

• These are often chained in forwards, branching or backwards manner to make an inference or a narrative

• (even quite classical) formal logics and annotation systems capture these

• Most AI/expert systems encode these, but rarely touch on scope (that is advanced AI) and never on Context


Conclusion


CSAR as a bridging structure between narrative text and behavioural rules

*IF* this structure turns out to be a useful and “natural” encoding of human narrative knowledge/expression then two steps are needed:

1. Techniques to capture/approximate/guess appropriate Cognitive Contexts and Scope judgments from Narrative Text

2. AI/Computer science architectures that make the encoding and use of CSAR structured knowledge

towards a context-sensitive structure for behavioural rules (context, scope, antecedents, and...

Education

evidence amp

sensitive

bruce edmonds

narrative

informal workshop

situational

cognitive

behavioural