首页|London Institute for Mathematical Sciences Researcher Adds New Data to Research in Neural Computation (Associative Learning and Active Inference)
London Institute for Mathematical Sciences Researcher Adds New Data to Research in Neural Computation (Associative Learning and Active Inference)
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Research findings on neural computatio n are discussed in a new report. According to news reporting out of the London I nstitute for Mathematical Sciences by NewsRx editors, research stated, "Associat ive learning is a behavioral phenomenon in which individuals develop connections between stimuli or events based on their co-occurrence." The news correspondents obtained a quote from the research from London Institute for Mathematical Sciences: "Initially studied by Pavlov in his conditioning exp eriments, the fundamental principles of learning have been expanded on through t he discovery of a wide range of learning phenomena. Computational models have be en developed based on the concept of minimizing reward prediction errors. The Re scorla- Wagner model, in particular, is a well-known model that has greatly influ enced the field of reinforcement learning. However, the simplicity of these mode ls restricts their ability to fully explain the diverse range of behavioral phen omena associated with learning. In this study, we adopt the free energy principl e, which suggests that living systems strive to minimize surprise or uncertainty under their internal models of the world. We consider the learning process as t he minimization of free energy and investigate its relationship with the Rescorl a-Wagner model, focusing on the informational aspects of learning, different typ es of surprise, and prediction errors based on beliefs and values."
London Institute for Mathematical Scienc esComputationEmerging TechnologiesMachine LearningNeural ComputationRe scorla-wagner Model
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