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Description
  • This paper integrates rigorous methods of reinforcement learning (RL) and control engineering with a behavioural (ethology) approach to the agent technology. The main outcome is a hybrid architecture for intelligent autonomous agents targeted to the Artificial Life like environments. The architecture adopts several biology concepts and shows that they can provide robust solutions to some areas. The resulting agents exhibit a wide range of behaviour from a simple primitive targeted behaviour to complex planning. The agent is fully autonomous through the environment feedback, evaluating internal agent state. This feedback motivates the agent to perform behaviours that return the agent towards optimal conditions
  • This paper integrates rigorous methods of reinforcement learning (RL) and control engineering with a behavioural (ethology) approach to the agent technology. The main outcome is a hybrid architecture for intelligent autonomous agents targeted to the Artificial Life like environments. The architecture adopts several biology concepts and shows that they can provide robust solutions to some areas. The resulting agents exhibit a wide range of behaviour from a simple primitive targeted behaviour to complex planning. The agent is fully autonomous through the environment feedback, evaluating internal agent state. This feedback motivates the agent to perform behaviours that return the agent towards optimal conditions (en)
Title
  • Ethological Concepts in Hierarchical Reinforcement Learning and Control of Intelligent Agents
  • Ethological Concepts in Hierarchical Reinforcement Learning and Control of Intelligent Agents (en)
skos:prefLabel
  • Ethological Concepts in Hierarchical Reinforcement Learning and Control of Intelligent Agents
  • Ethological Concepts in Hierarchical Reinforcement Learning and Control of Intelligent Agents (en)
skos:notation
  • RIV/68407700:21230/09:00165338!RIV10-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0567)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 313627
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/09:00165338
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  • artificial life; reinforcement learning; ethology; behavioral approach; agent; control; simulation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [912AFF4EBCDD]
http://linked.open...v/mistoKonaniAkce
  • Madrid
http://linked.open...i/riv/mistoVydani
  • Piscataway
http://linked.open...i/riv/nazevZdroje
  • 23rd European Conference on Modelling and Simulation
http://linked.open...in/vavai/riv/obor
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http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
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  • Nahodil, Pavel
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • IEEE
https://schema.org/isbn
  • 978-0-9553018-8-9
http://localhost/t...ganizacniJednotka
  • 21230
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