DARE Extended Architecture applied to

a Multi-Agent WorldMárcia Maçãs

DARE* Architecture

• Somatic Marker Theory (António Damásio)

– Decision as result of scenario anticipation based on past experience associated with body states that qualify them.

* Desenvolvimento de Agentes Robóticos Emocionais.

• Double Sensorial Processing (Joseph Ledoux)

– Fast, simple and reactive processing– Slow, complex and informed processing

• Goal of DARE Extension:– Apply the architecture to a dynamic multi-agent world;– Obtain adequate individual and social behaviours;

New Concepts

• Sympathy– Human ability to recognise others emotions, acquired by self-

awareness of their own emotions [Goleman, 1996].

– Evaluate others and predict their reactions based on a mental model which relates physical expressions with feelings and intentions, acquired by own experience or by observation.

• Non Verbal Communication – Emotional Expression

• Implicit

• Involuntary

• Informative

• Verbal Communication

Extended DARE Architecture

Agent

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ActionEffects

Perceptual Analysis

Symbolic Analysis

Cognitive Analysis

Built-inFeatures and

MeaningsMemoryBody

Multi-Agent World - Market

Product Examples

Agents Expressions Interface

Body or Internal State

• Agents Body or Internal State:

Internal State at instant t

Ideal Internal State

Unbalance at instant t

Perceptual Analysis

Perceptual Layer

Extraction of Relevant

FeaturesIp

Perceptual Evaluation

DVp ActionSelection

Action

ActionEffects

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BodyBuilt-in

Features andMeanings

- Weights relate colours and nutrients

- Ip and current Internal State

qualify stimuli - DVp

• Best Dv - Incentive Stimulus

• Reactive Selection given

• Ip, DVp e IS

Perceptual Layer

• Action EffectsAll data is stored in memory, including:

The action effects on Internal State are used to adapt (temporarily or not) the meaning functions from which results the DVp.

Perceptual Layer - Results

20 Simulations, 500 cycles of 5 seconds

Number of Internal State Changes

Mea

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axim

um U

nbal

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ConditionedExecution

Cognitive Layer

Cognitive Analysis

Feature Extraction

IcCognitiveEvaluation

Actions& Body

ActionSelection

Action

ActionEffects

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BodyMemory

DVp intervals that reveal urgency: Stimulus x IS

Search in memory for the best action to execute given the current IS

and past effects.

-Memory structure – Sequences

-Selection of action belonging to matched sequence which minimizes the unbalance in the end.

Results

20 Simulations, 500 cycles of 5 seconds

Number of Internal State Changes

Mea

n o

f M

axim

um U

nbal

ance

Conditioned Execution

Symbolic Layer

Symbolic Analysis

Feature Extraction

IsSymbolicEvaluation

Actions& Body

ActionSelection

Action

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BodyMemory

ActionEffects

• OntologyMaps features and symbols:

•Descriptive symbols (set of features)

•Identifier symbols (name of a set of descriptive symbols)

Syntactic knowledge about messages.

Symbolic Layer

• Expanded Internal State• Elements not directly related to survival

• Internal Representation of the Agent itself• Necessary for sympathy and non-verbal communication

• There is an image of itself on each layer

Symbolic Layer• Symbolic Evaluation and Action Selection

– Specific Actions in this Layer:

• Communication.

– Memory includes

• Symbolic information

• Expanded Internal State

– Sequences include:• Own experience • Other agents observed experience

– Dialogs that end with expression change

– Action is executed if belongs to sequence with an ending expression similar to the ideal one

Symbolic Layer - Results

Symbolic Layer - Results

Order

• Long term goals and cooperation

• Ask for product

• If supplier has good recall of the product sympathises and starts negotiation.

• Supplier assumes a fictitious internal state identical to the past and searches the product.

Symbolic Layer - Results

Conclusion and Future Work

• The adaptation on the perceptual layer allows a best performance of the overall architecture;

• The cognitive layer allows flexible behaviour and more accurate learning;

• The symbolic layer allows communication and the emergence of cooperation/concurrence behaviours.

In the application of DARE architecture to a multi-agent world:

Future Work • Long term anticipation of the internal state.• Inference mechanisms triggered by internal

stimuli.• Learning of Expression-Internal state relation.• Improvements on memory managing