{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:27:29Z","timestamp":1740202049017,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"abstract":"<jats:p>In reinforcement learning (RL), an important sub-problem is learning the value function, which is chiefly influenced by the architecture used to represent value functions. is often expressed as a linear combination of a pre-selected set of basis functions. These basis functions are either selected in an ad-hoc manner or are tailored to the RL task using the domain knowledge. Selecting basis functions in an ad-hoc manner does not give a good approximation of value function while choosing functions using domain knowledge introduces dependency on the task. Thus, a desirable scenario is to have a method to choose basis functions that are task independent, but which also provide a good approximation for the value function. In this paper, we propose a novel task-independent basis function construction method that uses the topology of the underlying state space and the reward structure to build the reward-based Proto Value Functions (RPVFs). The approach we propose gives good approximation for the value function and enhanced learning performance. The performance is demonstrated via experiments on grid-world tasks.<\/jats:p>","DOI":"10.3233\/978-1-61499-672-9-1690","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:24Z","timestamp":1740133644000},"source":"Crossref","is-referenced-by-count":0,"title":["Shaping Proto-Value Functions Using Rewards"],"prefix":"10.3233","author":[{"family":"Maity Raj Kumar","sequence":"additional","affiliation":[]},{"family":"Lakshminarayanan Chandrashekar","sequence":"additional","affiliation":[]},{"family":"Padakandla Sindhu","sequence":"additional","affiliation":[]},{"family":"Bhatnagar Shalabh","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2016"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:06:00Z","timestamp":1740135960000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-671-2&spage=1690&doi=10.3233\/978-1-61499-672-9-1690"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-672-9-1690","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2016]]}}}