Decentralized stochastic planning with anonymity in interactions
In this paper, we solve cooperative decentralized stochastic planning problems, where the interactions between agents (specified using transition and reward functions) are dependent on the number of agents (and not on the identity of the individual agents) involved in the interaction. A collision...
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Association for the Advancement of Artificial Intelligence (AAAI)
2015
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| Online Access: | http://hdl.handle.net/1721.1/100438 https://orcid.org/0000-0002-8585-6566 |
| _version_ | 1826192721636753408 |
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| author | Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick |
| author_sort | Varakantham, Pradeep |
| collection | MIT |
| description | In this paper, we solve cooperative decentralized stochastic planning problems, where the interactions between agents (specified using transition and reward functions) are dependent on the number of agents (and not on the identity of the individual agents) involved in the interaction. A collision of robots in a narrow corridor, defender teams coordinating patrol activities to secure a target, etc. are examples of such anonymous interactions. Formally, we consider problems that are a subset of the well known Decentralized MDP (DEC-MDP) model, where the anonymity in interactions is specified within the joint reward and transition functions. In this paper, not only do we introduce a general model model called D-SPAIT to capture anonymity in interactions, but also provide optimization based optimal and local-optimal solutions for generalizable sub-categories of D-SPAIT. |
| first_indexed | 2024-09-23T09:28:13Z |
| format | Article |
| id | mit-1721.1/100438 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:28:13Z |
| publishDate | 2015 |
| publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
| record_format | dspace |
| spelling | mit-1721.1/1004382022-09-30T14:37:26Z Decentralized stochastic planning with anonymity in interactions Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Jaillet, Patrick In this paper, we solve cooperative decentralized stochastic planning problems, where the interactions between agents (specified using transition and reward functions) are dependent on the number of agents (and not on the identity of the individual agents) involved in the interaction. A collision of robots in a narrow corridor, defender teams coordinating patrol activities to secure a target, etc. are examples of such anonymous interactions. Formally, we consider problems that are a subset of the well known Decentralized MDP (DEC-MDP) model, where the anonymity in interactions is specified within the joint reward and transition functions. In this paper, not only do we introduce a general model model called D-SPAIT to capture anonymity in interactions, but also provide optimization based optimal and local-optimal solutions for generalizable sub-categories of D-SPAIT. Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology Center. Future Urban Mobility Program) 2015-12-18T16:42:05Z 2015-12-18T16:42:05Z 2014-07 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/100438 Varakantham, Pradeep, Yossiri Adulyasak, and Patrick Jaillet. "Decentralized stochastic planning with anonymity in interactions." 28th AAAI Conference on Artificial Intelligence (July 2014). https://orcid.org/0000-0002-8585-6566 en_US http://easychair.org/smart-program/AAAI-14/2014-07-30.html Proceedings of the 28th AAAI Conference on Artificial Intelligence Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for the Advancement of Artificial Intelligence (AAAI) MIT web domain |
| spellingShingle | Varakantham, Pradeep Adulyasak, Yossiri Jaillet, Patrick Decentralized stochastic planning with anonymity in interactions |
| title | Decentralized stochastic planning with anonymity in interactions |
| title_full | Decentralized stochastic planning with anonymity in interactions |
| title_fullStr | Decentralized stochastic planning with anonymity in interactions |
| title_full_unstemmed | Decentralized stochastic planning with anonymity in interactions |
| title_short | Decentralized stochastic planning with anonymity in interactions |
| title_sort | decentralized stochastic planning with anonymity in interactions |
| url | http://hdl.handle.net/1721.1/100438 https://orcid.org/0000-0002-8585-6566 |
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