The Dynamics of Active Categorical Perception in an Evolved Model Agent

Beer, Randall D.

doi:10.1177/1059712303114001

Cited by 392 publications

(382 citation statements)

References 55 publications

Supporting

Mentioning

358

Contrasting

Unclassified

Order By: Relevance

“…It would also be instructive to use exactly the same tools and the same parameters to evolve foragers with different types of controllers, such as continuous time recurrent neural networks, as in Refs. [37,81,82], or radically different ones such as the Markov networks in [83,84] and see what previous evolutionary obstacles they ease, or which new ones they impose.…”

Section: Resultsmentioning

confidence: 99%

Evolution of sustained foraging in three-dimensional environments with physics

Chaumont¹,

Adami

2016

Genet Program Evolvable Mach

View full text Add to dashboard Cite

Artificially evolving foraging behavior in simulated articulated animals has proved to be a notoriously difficult task. Here, we co-evolve the morphology and controller for virtual organisms in a three-dimensional physical environment to produce goal-directed locomotion in articulated agents. We show that following and reaching multiple food sources can evolve de novo, by evaluating each organism on multiple food sources placed on a basic pattern that is gradually randomized across generations. We devised a strategy of evolutionary ''staging'', where the best organism from a set of evolutionary experiments using a particular fitness function is used to seed a new set, with a fitness function that is progressively altered to better challenge organisms as evolution improves them. We find that an organism's efficiency at reaching the first food source does not predict its ability at finding subsequent ones because foraging efficiency crucially depends on the position of the last food source reached, an effect illustrated by ''foraging maps'' that capture the organism's controller state, body position, and orientation. Our best evolved foragers are able to reach multiple food sources over 90 % of the time on average, a behavior that is key to any biologically realistic simulation where a self-sustaining population has to survive by collecting food sources in three-dimensional, physical environments.Electronic supplementary material The online version of this article

show abstract

Section: Resultsmentioning

confidence: 99%

Evolution of sustained foraging in three-dimensional environments with physics

Chaumont¹,

Adami

2016

Genet Program Evolvable Mach

View full text Add to dashboard Cite

show abstract

“…to detect the duration of a given sensory state) and/or to remember and eventually communicate previously experienced sensory states (Beer, 2003;Nolfi and Marocco, 2001). In other words, the characteristics of the neural controllers potentially allow the robots to extract and communicate information that is not currently available through their sensors.…”

Section: N F R a R E D V I S I O N C O Mmu N I C A T I O N C O Mmu mentioning

confidence: 99%

Evolution of Implicit and Explicit Communication in Mobile Robots

Greeff

Nolfi

2009

Evolution of Communication and Language in Embodied Agents

View full text Add to dashboard Cite

Abstract. This work investigates the conditions in which a population of embodied agents evolved for the ability to display coordinated/cooperative skills can develop an ability to communicate, whether and to what extent the evolved communication system can complexifies during the course of the evolutionary process, and how the characteristics of such communication system varies evolutionarily. The analysis of the obtained results indicates that evolving robots develop a capacity to access/generate information which has a communicative value, an ability to produce different signals encoding useful regularities, and an ability to react appropriately to explicit and implicit signals. The analysis of the obtained results allows us to formulate detailed hypothesis on the evolution of communication for what concern aspects such us: (i) how communication can emerge from a population of initially noncommunicating agents, (ii) how communication systems can complexifies, (iii) how signals/meanings can originate and how they can be grounded in agents sensory-motor states.

show abstract

“…For example, dynamical systems studies combined with artificial evolution of algorithms for control of real or simulated agents (evolutionary robotics or evolutionary computation, respectively) suggest that the number of neurons required to simulate a minimal cognitive feat is exceedingly small. Continuous-time recurrent neural networks can be artificially evolved to undertake perceptual categorization of falling 'triangles' and 'squares' using active vision with only eight neurons [82]. Relational categorization of concepts such as larger or smaller can be achieved using five neurons [83].…”

Section: What Is Cognitive Complexity and How Does It Evolve?mentioning

confidence: 99%

What is comparable in comparative cognition?

Chittka

Rossiter

Skorupski

et al. 2012

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

To understand how complex, or 'advanced' various forms of cognition are, and to compare them between species for evolutionary studies, we need to understand the diversity of neural-computational mechanisms that may be involved, and to identify the genetic changes that are necessary to mediate changes in cognitive functions. The same overt cognitive capacity might be mediated by entirely different neural circuitries in different species, with a many-to-one mapping between behavioural routines, computations and their neural implementations. Comparative behavioural research needs to be complemented with a bottom-up approach in which neurobiological and molecular-genetic analyses allow pinpointing of underlying neural and genetic bases that constrain cognitive variation. Often, only very minor differences in circuitry might be needed to generate major shifts in cognitive functions and the possibility that cognitive traits arise by convergence or parallel evolution needs to be taken seriously. Hereditary variation in cognitive traits between individuals of a species might be extensive, and selection experiments on cognitive traits might be a useful avenue to explore how rapidly changes in cognitive abilities occur in the face of pertinent selection pressures.

show abstract

The Dynamics of Active Categorical Perception in an Evolved Model Agent

Cited by 392 publications

References 55 publications

Evolution of sustained foraging in three-dimensional environments with physics

Evolution of sustained foraging in three-dimensional environments with physics

Evolution of Implicit and Explicit Communication in Mobile Robots

What is comparable in comparative cognition?

Contact Info

Product

Resources

About