6533b873fe1ef96bd12d4c08

RESEARCH PRODUCT

Some Effects of Individual Learning on the Evolution of Sensors

Thomas UthmannTobias JungPeter Dauscher

subject

Basis (linear algebra)business.industryComputer scienceIndividual learningEvolutionary algorithmReinforcement learningMarkov decision processArtificial intelligencebusinessAdaptation (computer science)

description

In this paper, we present an abstract model of sensor evolution, where sensor development is only determined by artificial evolution and the adaptation of agent reactions is accomplished by individual learning. With the environment cast into a MDP framework, sensors can be conceived as a map from environmental states to agent observations and Reinforcement Learning algorithms can be utilised. On the basis of a simple gridworld scenario, we present some results of the interaction between individual learning and evolution of sensors.

yearjournalcountryeditionlanguage
2001-01-01
https://doi.org/10.1007/3-540-44811-x_47