Rigid reduced successor representation as a potential mechanism for addiction
نویسندگان
چکیده
منابع مشابه
Running head: SUCCESSOR REPRESENTATION and TEMPORAL CONTEXT The Successor Representation and Temporal Context
The successor representation was introduced into reinforcement learning by Dayan (1993) as a means of facilitating generalization between states with similar successors. Although reinforcement learning in general has been used extensively as a model of psychological and neural processes, the psychological validity of the successor representation has yet to be explored. An interesting possibilit...
متن کاملThe Successor Representation and Temporal Context
The successor representation was introduced into reinforcement learning by Dayan ( 1993 ) as a means of facilitating generalization between states with similar successors. Although reinforcement learning in general has been used extensively as a model of psychological and neural processes, the psychological validity of the successor representation has yet to be explored. An interesting possibil...
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Options in reinforcement learning allow agents to hierarchically decompose a task into subtasks, having the potential to speed up learning and planning. However, autonomously learning effective sets of options is still a major challenge in the field. In this paper we focus on the recently introduced idea of using representation learning methods to guide the option discovery process. Specificall...
متن کاملThe successor representation in human reinforcement learning
Theories of reward learning in neuroscience have focused on two families of algorithms, thought to capture deliberative vs. habitual choice. “Model-based” algorithms compute the value of candidate actions from scratch, whereas “model-free” algorithms make choice more efficient but less flexible by storing pre-computed action values. We examine an intermediate algorithmic family, the successor r...
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Estimation of returns over time, the focus of temporal difference (TD) algorithms, imposes particular constraints on good function approximators or representations. Appropriate generalisation between states is determined by how similar their successors are, and representations should follow suit. This paper shows howTDmachinery can be used to learn such representations, and illustrates, using a...
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ژورنال
عنوان ژورنال: European Journal of Neuroscience
سال: 2021
ISSN: 0953-816X,1460-9568
DOI: 10.1111/ejn.15227