roma, meeting mindraces 2-3 october 2006 istc-cnr achievements mindraces: from reactive to...

Roma, Meeting Mindraces 2-3 October 2006

ISTC-CNR Achievements

MindRACES: From Reactive to Anticipatory Cognitive Embodied Systems (FP6-511931)


Which is our goal

Scenario: Guards and Thieves Architecture of the Guard:

1. Intention Management • goals are selected on the basis of reasons, i.e. beliefs • an adopted goal corresponds now the activation of an Intention

(intend to do a certain action/plan realizing the goal)

2. Planning • Once an Intention is adopted, the Planner selects/builds a suitable

course of actions to achieve it

3. Actuation and Adaptation • actuation of the plans by the means of sensorimotor interactions

any action, even if deliberated and planned, in order to be realized has to be implemented by the means of low level, sensorimotor interactions


The Role of Expectations

low level: directly matched with perceptions short ranged

strategic planning select among goals and plans long-ranged not matched with perceptions, but with goals


Current work

Actuation and adaptation Presented at SAB 2006

Development of concepts and abstraction Presented ad EPIROB 2006

Intention management and planning To be presented at IJCAI 2007


Actuation and Adaptation


Schema Based Design

Two kinds of schemas: perceptual schemas and motor schemas

Arbib (1992), Arkin et al. (2000), Piaget (1954), Roy (2005)

agent

environment


Expectations matched with Perception


Cooperation between schemas

Typically many schemas cooperate for realizing one behavior… …but “mixed” courses of actions also emerge from the contribute

of schemas realizing different behaviors

Red = avoid obstacleBlue = stay in path


Competition between behaviors

Red = fearBlue = detect predatorBlack = detect prey


Effects of Drives

not very hungry very hungry


Anticipatory vs. Reactive Systems

MANTIS already described

MANTIS-R not using prediction for assigning priority


Development of Concepts


Developing Simulators/Categories

Simulator = cluster of schemas

perceptual and motor schemas having coordinated patterns of prediction evolve energetic links

differential hebbian learning coherence in prediction informativeness

schemas can spread activation to each other via the evolved links

distributed architecture K-means cluster analysis

(euclidean distance of activity level): 16 clusters for 20 insects


Developing categories for abstract entities

We introduced two drives: fear and hunger Two nodes in a Fuzzy Cognitive Map (Kosko 1992) with

inhibitory links …and let the system leanr new schemas for avoiding We divided insects into predators and preys…

close predators increase fear, absence of predators decreases it close preys + a biological clock increase hunger, reaching preys

decreases it …and used again differential hebbian learning

fear evolves links with schemas for avoiding; hunger with following

Abstraction = the role played by entities A new way of clustering entities according to the needs of the

agent

Kosko, B. (1992). Neural Networks and Fuzzy Systems. Prentice Hall International, Singapore.


Intentions Managementand planning


Intention Management

•Competing goals: •Have V, escape guard•-> Have V•Plan: find V•Subgoal: search living•Plan: pass 5


Intention Management


Future Work: bridging the gap from actuation to intentionality1. Long term expectations and evaluations

Planning = evaluating/comparing alternative courses of actions

schema --> success long term effects

evaluation2. Hierarchies

3. From Drives to Goals


Thank You!

contact: [email protected]: From Reactive to Anticipatory Cognitive Embodied Systems (FP6-511931)

roma, meeting mindraces 2-3 october 2006 istc-cnr achievements mindraces: from reactive to...

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