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Evolution/Development of Actionand LanguageStefano NolfiLaboratory of Autonomous Robotics and Artificial LifeInstitute of Cognitive Sciences and Technologies, CNRRoma, Italy

1. Theoretical backgroundOutline & Objectives2. How population of evolving robots can co-develop behavioral andcommunication skillsHow signals and “meanings” emergeHow the development of action skill support the developmentof communication skills and vice versa3. How robots can acquire early language comprehension capabilitiesHow robots can display compositional language/action skillsHow language exposure and self-talk facilitate actiondevelopment4. Discussion and Conclusions

Theoretical HypothesisBehavior and cognition are complex adaptivesystems characterized by emergent properties andby a multi-level and multi-scale organization

Behavior and Cognition as Dynamical SystemsBehavior & CognitionEnvironmentBodyNervousSystemBehaviour and cognition aredynamical processes that extend overtime and result from a large numberof robot/environmental interactionsoccurring at a fast time rate betweenthe robot’s control system, body, andthe physical and social environment.

ehaviorbehaviorBehavior and Cognition as Complex Multi-Leveland Multi-Scale Dynamical SystemsbehaviorbehaviorEnvironmentBodyNervousSystembehavior(i) The interactions between lowerlevelprocesses (that extend for alimited time duration) give rise tohigher-level processes (thatextend for longer time spans)(ii) higher-level processes lateraffect the lower-level processesfrom which they originatebehavior

ehaviorbehaviorBehavior and Cognition as Adaptive SystemsSystems with varying fine-grained characteristics in which variations areretained or discarded on the basis of the their effects at the level of theoverall behavior produced by the agent in interaction with thephysical/social environment.behaviorbehaviorselectionTo adapt to variation of thetask/environmentEnvironmentBodyNervousSystembehaviorvariationsTo synthesize functions emergingfrom the interactions of lower-levelscomponents among themselvesand with the environment.behavior

Evolution of behavioral and communication skills ingroups of cooperating robotswheelsspeakerinfraredgroundvisionmicrophoneFitness Function: The group is reward with 1 point every time the robots areconcurrently located in the two areas for the first time or after a switchDe Greef & Nolfi, 2010

De Greef & Nolfi, 2010

Summary of the main evolutionary progressesnavigate-to-whitelook-robot-and-follow-borderInfrared-off -> move-forwardInfrared-on -> avoid-obstaclesmove-f. & avoid-ob. -> find areasexit-from-white-areatoward exit-from-white-areathe other robotremain-on-white-areaobstacle-avoidanceDe Greef & Nolfi, 2010.navigate-to-blacksignal A/Bremain-on-black-areafind-areasmove-forwardground-black -> remain on the blackarea look-robot-and-follow-borderground-white/black -> signal A/Bexit-from-black-area Sound-B & ground-black -> exitfrom black areaSound-A & ground-white -> remainon white area follow borderSound-B & ground-white -> & exit seerobotfrom white -> exit area from white area towardthe other robotexit from white & move-f ->navigate-to-blacklook-r.-follow-b. & & move-f ->navigate-to-white

Multi-level formation, innovations, incrementality &complexificationnavigate-to-whitelook-robot-and-follow-bordernavigate-to-blackexit-from-white-areatoward exit-from-white-areathe other robotexit-from-black-arearemain-on-white-areasignal A/Bremain-on-black-areafind-areasobstacle-avoidancemove-forwardNew higher-level capacitiesemerge through the interactionsbetween pre-existing skills orthrough new traits combined withskill re-useInnovations are enabled by thenew adaptive opportunitiescreated by the effects of agents’behaviors and by the possibilityto re-use existing capacityOld skills (assuming newfunctions) tend to be preservedthus leading to an incrementalprocessDe Greef & Nolfi, 2010.

Language and action integration and synergiesbetween language and action developmentnavigate-to-whitelook-robot-and-follow-bordernavigate-to-blackexit-from-white-areatoward exit-from-white-areathe other robotexit-from-black-arearemain-on-white-areaSignals/meanings originatethrough the development (andare grounded in) behavioral skillsSignals constitute one of themain drive enabling thedevelopment of new behavioralskills.signal A/Bremain-on-black-areafind-areasobstacle-avoidancemove-forwardDe Greef & Nolfi, 2010.

Development of early language comprehensioncapabilitiesS 1 S 2T l T r Vision Obj. & Act. LabelsFitness: The robot is rewardedfor the ability to realize thegoals of the experiencedutterances.INDICATEIGNORETOUCHMOVEBLUE RED GREENYES YES YESYES YES NONO YES YESTuci, Ferrauto, Zeschel, Massera, Nolfi (2009, 2011)

Development of early language comprehensioncapabilitiesINDICATE REDTOUCH YELLOWGRASP REDFerrauto and Nolfi (2012)

Tuci, Ferrauto, Arne, Massera, Nolfi (2010, 2011)Generalization in Comprehension and Action ProductionBy post-evaluating the robots at the end of the training process withobserved that some of them display an ability to comprehend the twonew utterances by displaying the corresponding appropriate behaviors.indicate-redEnvironmentBodyRobots trained to producerelated skills tend to lead tosolutions based on multi-levelorganizations supporting skillre-combination and re-use.ControlSystemindicate-green

Language exposure and self-talk facilitatesaction developmentSignificantly facilitates the capacity to acquire high-level behaviors(e.g. moving a object to a basked) by combining a set of lower-levelbehavior (reaching-object, grasping, reaching-target, releasing-object)

Discussion 1/2An important challenge for scaling ER methods toward real-worldapplications concerns the development of agents displaying severalintegrated capacities and possibly able to expand their capacityrepertoire overt time.The multi-level organization of behavioral and cognitive skills:Enable generalization and compositionality at the level of behaviorsFacilitate the development of new skills through competence re-useSupport incremental processes leading to a progressive expansionof the agents’ capacities repertoire

Discussion 2/2Communication/language and action are two tightly integratedphenomena.The interaction between adaptive agents and humans mediated bysymbolic interactions can allow the former to develop richer and morecomplex capacities.

AcknowledgementsJoachim De Greeff MasseraCognitive Systems and RoboticsTomassino FerrautoElio Tuciwww.ecagents.orgFuture and Emerging TechnologiesOnofrio GigliottaTobias Leugger

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