Learning to Perceive and Act by Trial and Error
Machine Learning
Embedded neural networks: exploiting constraints
Neural Networks - Special issue on neural control and robotics: biology and technology
Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms
The 3rd International Symposium on Experimental Robotics III
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One important implication of embodiment is that, by acting, agents partially determine the sensory patterns they receive from the environment. The motor actions performed by an agent, by modifying the agent's position with respect to the external environment and/or the external environment itself, partially determine the type of sensory patterns received from the environment In this paper we investigate how agents can take advantage of this abilify. In particular, we discuss how agents coordinate sensory and motor processes in order to (1) select sensory patterns which are not affected by the aliasing problem and avoid those which are; (2) select sensory patterns such that groups of patterns which require different responses do not strongly overlap; (3) exploit emergent behaviors that result from the interaction between the agent and the environment.