{"type":"ScholarlyArticle","title":"Intention Progression under Uncertainty","authors":[{"name":"Yuan Yao","slug":"yuan-yao","given":"Yuan","family":"Yao","affiliation":"College of Computer Science and Technology , Zhejiang University of Technology"},{"name":"Natasha Alechina","slug":"natasha-alechina","given":"Natasha","family":"Alechina","affiliation":"Department of Information and Computing Sciences , University of Utrecht"},{"name":"Brian Logan","slug":"brian-logan","given":"Brian","family":"Logan","affiliation":"School of Computer Science , University of Nottingham"},{"name":"John Thangarajah","slug":"john-thangarajah","given":"John","family":"Thangarajah","affiliation":"School of Science , RMIT University"}],"abstract":"A key problem in Belief-Desire-Intention agents is how an agent progresses its intentions, i.e., which plans should be selected and how the execution of these plans should be interleaved so as to achieve the agent’s goals. Previous approaches to the intention progression problem assume the agent has perfect information about the state of the environment. However, in many real-world applications, an agent may be uncertain about whether an environment condition holds, and hence whether a particular plan is applicable or an action is executable. In this paper, we propose SAU, a Monte-Carlo Tree Search (MCTS)-based scheduler for intention progression problems where the agent’s beliefs are uncertain. We evaluate the performance of our approach experimentally by varying the degree of uncertainty in the agent’s beliefs. The results suggest that SAU is able to successfully achieve the agent’s goals even in settings where there is significant uncertainty in the agent’s beliefs.","doi":"10.24963/ijcai.2020/2","url":"https://ijcai.org/proceedings/2020/2","pdf":"https://ijcai.org/proceedings/2020/0002.pdf","markdown":"https://ijcai.org/proceedings/2020/2.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/2","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Agent-based and Multi-agent Systems","track":"Main track","number":2,"pages":{"first":10,"last":16},"keywords":["Agent-based and Multi-agent Systems: Agent Theories and Models","Agent-based and Multi-agent Systems: Engineering Methods, Platforms, Languages and Tools"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/25063/file_25063.m3u8","length_sec":298,"provider":"hls"}],"references":[{"position":1,"raw":"[Bauters et al., 2014] Kim Bauters, Weiru Liu, Jun Hong, Carles Sierra, and Lluis Godo. CAN(PLAN)+: extending the operational semantics of the BDI architecture to deal with uncertain information. In 30th Conference on Uncer- tainty in Artificial Intelligence, pages 52-61. AUAI Press, 2014.","title":"CAN(PLAN)+: extending the operational semantics of the BDI architecture to deal with uncertain information","authors":"Kim Bauters, Weiru Liu, Jun Hong, Carles Sierra, Lluis Godo","year":"2014","venue":"30th Conference on Uncertainty in Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bitan and Kraus, 2018] Moshe Bitan and Sarit Kraus. Com- bining prediction of human decisions with ISMCTS in im- perfect information games. In 17th International Con- ference on Autonomous Agents and MultiAgent Systems, pages 1874-1876. IFAAMAS/ACM, 2018.","title":"Combining prediction of human decisions with ISMCTS in imperfect information games","authors":"Kraus Bitan, Moshe Bitan, Sarit Kraus","year":"2018","venue":"17th International Con-ference on Autonomous Agents and MultiAgent Systems","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Bjarnason et al., 2009] Ronald Bjarnason, Alan Fern, and Prasad Tadepalli. Lower bounding Klondike Solitaire with Monte-Carlo Planning. In 19th International Conference on Automated Planning and Scheduling. AAAI, 2009.","title":"Lower bounding Klondike Solitaire with Monte-Carlo Planning","authors":"Ronald Bjarnason, Alan Fern, Prasad Tadepalli","year":"2009","venue":"19th International Conference on Automated Planning and Scheduling","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Browne et al., 2012] Cameron Browne, Edward Jack Pow- ley, Daniel Whitehouse, and et al. A survey of Monte Carlo Tree Search methods. IEEE Transactions on Computa- tional Intelligence and AI in Games, 4(1):1-43, 2012.","title":"A survey of Monte Carlo Tree Search methods","authors":"Cameron Browne, Edward Jack Powley, Daniel Whitehouse","year":"2012","venue":"IEEE Transactions on Computational Intelligence and AI in Games","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Casali et al., 2011] Ana Casali, Lluis Godo, and Carles Sierra. A graded BDI agent model to represent and reason about preferences. Artificial Intelligence, 175(7-8):1468- 1478, 2011.","title":"A graded BDI agent model to represent and reason about preferences","authors":"Ana Casali, Lluis Godo, Carles Sierra","year":"2011","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Coelho and Nogueira, 2015] Francisco Coelho and Vítor Nogueira. Probabilistic perception revision in agents- peak(l). In PRIMA 2015: Principles and Practice of Multi- Agent Systems, volume 9387 of LNCS, pages 613-621. Springer, 2015.","title":"Francisco Coelho and Vítor Nogueira. Probabilistic perception revision in agentspeak(l)","authors":"Nogueira Coelho","year":"2015","venue":"PRIMA 2015: Principles and Practice of Multi-Agent Systems","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Fagundes et al., 2009] Moser Silva Fagundes, Rosa Maria Vicari, and Helder Coelho. Deliberation process in a BDI model with bayesian networks. In PRIMA 2009: Princi- ples and Practice of Multi-Agent Systems, volume 5044 of LNCS, pages 207-218. Springer, 2009.","title":"Deliberation process in a BDI model with bayesian networks","authors":"Silva Moser, Rosa Maria Fagundes, Helder Vicari, Coelho","year":"2009","venue":"PRIMA 2009: Principles and Practice of Multi-Agent Systems","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Kocsis and Szepesvári, 2006] Levente Kocsis and Csaba Szepesvári. Bandit based Monte-Carlo planning. In 17th European Conference on Machine Learning, pages 282- 293. Springer, 2006.","title":"Bandit based Monte-Carlo planning","authors":"Szepesvári Kocsis, Levente Kocsis, Csaba Szepesvári","year":"2006","venue":"17th European Conference on Machine Learning","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Kwisthout and Dastani, 2005] Johan Kwisthout and Mehdi Dastani. Modelling uncertainty in agent programming. In 3rd International Workshop on Declarative Agent Lan- guages and Technologies, volume 3904 of LNCS, pages 17-32. Springer, 2005.","title":"Modelling uncertainty in agent programming","authors":"Dastani Kwisthout, Johan Kwisthout, Mehdi Dastani","year":"2005","venue":"3rd International Workshop on Declarative Agent Languages and Technologies","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Logan et al., 2017] Brian Logan, John Thangarajah, and Neil Yorke-Smith. Progressing intention progression: A call for a goal-plan tree contest. In 16th Conference on Autonomous Agents and MultiAgent Systems, pages 768- 772. IFAAMAS, 2017.","title":"Progressing intention progression: A call for a goal-plan tree contest","authors":"Brian Logan, John Thangarajah, Neil Yorke-Smith","year":"2017","venue":"16th Conference on Autonomous Agents and MultiAgent Systems","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Ma et al., 2014] Jianbing Ma, Weiru Liu, Jun Hong, Lluis Godo, and Carles Sierra. Plan selection for probabilis- tic BDI agents. In 26th IEEE International Conference on Tools with Artificial Intelligence, pages 83-90. IEEE, 2014.","title":"Plan selection for probabilistic BDI agents","authors":"Ma","year":"2014","venue":"26th IEEE International Conference on Tools with Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Pearl, 1988] Judea Pearl. Probabilistic Reasoning in Intel- ligent Systems. Morgan Kaufmann, 1988. [Pěchouček and Mařík, 2008] Michal Pěchouček and Vladimír Mařík. Industrial deployment of multi-agent technologies: Review and selected case studies. Au- tonomous Agents and Multi-Agent Systems, 17:397-431, 2008.","title":"Judea Pearl. Probabilistic Reasoning in Intelligent Systems","authors":"Pearl","year":"1988","venue":"Autonomous Agents and Multi-Agent Systems","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Rao and Georgeff, 1992] Anand S. Rao and Michael P. Georgeff. An abstract architecture for rational agents. In 3rd International Conference on Principles of Knowledge Representation and Reasoning, pages 439-449.","title":"An abstract architecture for rational agents","authors":"Anand S Rao, Michael P Georgeff","year":null,"venue":"3rd International Conference on Principles of Knowledge Representation and Reasoning","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Morgan Kaufmann, 1992. Schut et al., 2001] Martijn C. Schut, Michael J. Wooldridge, and Simon Parsons. Reasoning about intentions in uncertain domains. In 6th European Con- ference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, volume 2143 of LNCS, pages 84-95. Springer, 2001.","title":"Reasoning about intentions in uncertain domains","authors":"C Martijn, Michael J Schut, Simon Wooldridge, Parsons","year":"2001","venue":"6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Silva and Gluz, 2011] Diego Goncalves Silva and Joao Car- los Gluz. AgentSpeak(PL): A new programming language for BDI agents with integrated bayesian network model. In International Conference on Information Science and Applications. IEEE, 2011.","title":"Diego Goncalves Silva and Joao Carlos Gluz. AgentSpeak(PL): A new programming language for BDI agents with integrated bayesian network model","authors":"Gluz Silva","year":"2011","venue":"International Conference on Information Science and Applications","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Tesauro et al., 2010] Gerald Tesauro, V. T. Rajan, and Richard Segal. Bayesian inference in Monte-Carlo Tree Search. In 26th Conference on Uncertainty in Artificial Intelligence, pages 580-588. AUAI Press, 2010.","title":"Bayesian inference in Monte-Carlo Tree Search","authors":"V T Gerald Tesauro, Richard Rajan, Segal","year":"2010","venue":"26th Conference on Uncertainty in Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Thangarajah and Padgham, 2011] John Thangarajah and Lin Padgham. Computationally Effective Reasoning About Goal Interactions. Journal of Automated Reason- ing, 47(1):17-56, 2011.","title":"Computationally Effective Reasoning About Goal Interactions","authors":"Padgham Thangarajah, John Thangarajah, Lin Padgham","year":"2011","venue":"Journal of Automated Reasoning","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Thangarajah et al., 2003] John Thangarajah, Lin Padgham, and Michael Winikoff. Detecting & Avoiding Interfer- ence Between Goals in Intelligent Agents. In 18th Inter- national Joint Conference on Artificial Intelligence, pages 721-726.","title":"Detecting & Avoiding Interference Between Goals in Intelligent Agents","authors":"John Thangarajah, Lin Padgham, Michael Winikoff","year":null,"venue":"18th International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2003/105"},{"position":19,"raw":"Morgan Kaufmann, 2003.","title":null,"authors":"Morgan Kaufmann","year":"2003","venue":null,"doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Waters et al., 2014] Max Waters, Lin Padgham, and Sebas- tian Sardina. Evaluating coverage based intention selec- tion. In 13th International Conference on Autonomous Agents and Multi-agent Systems, pages 957-964.","title":"Evaluating coverage based intention selection","authors":"Waters","year":"2014","venue":"13th International Conference on Autonomous Agents and Multi-agent Systems","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Waters et al., 2015] Max Waters, Lin Padgham, and Sebas- tian Sardiña. Improving domain-independent intention se- lection in BDI systems. Autonomous Agents and Multi- Agent Systems, 29(4):683-717, 2015.","title":"Improving domain-independent intention selection in BDI systems","authors":"Waters","year":"2015","venue":"Autonomous Agents and Multi-Agent Systems","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Whitehouse et al., 2011] Daniel Whitehouse, Edward Jack Powley, and Peter I. Cowling. Determinization and in- formation set Monte Carlo Tree Search for the card game Dou Di Zhu. In IEEE Conference on Computational Intel- ligence and Games, pages 87-94. IEEE, 2011.","title":"Determinization and information set Monte Carlo Tree Search for the card game Dou Di Zhu","authors":"Daniel Whitehouse, Edward Jack Powley, Peter I Cowling","year":"2011","venue":"IEEE Conference on Computational Intelligence and Games","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Yao and Logan, 2016] Yuan Yao and Brian Logan. Action- level intention selection for BDI agents. In 15th Interna- tional Conference on Autonomous Agents and Multiagent Systems, pages 1227-1236. IFAAMAS, 2016.","title":"Actionlevel intention selection for BDI agents","authors":"Logan ; Yao, Yuan Yao, Brian Logan","year":"2016","venue":"15th International Conference on Autonomous Agents and Multiagent Systems","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Yao et al., 2014] Yuan Yao, Brian Logan, and John Thangarajah. SP-MCTS-based intention scheduling for BDI agents. In 21st European Conference on Artificial Intelligence, pages 1133-1134. IOS Press, 2014.","title":"SP-MCTS-based intention scheduling for BDI agents","authors":"Yuan Yao, Brian Logan, John Thangarajah","year":"2014","venue":"21st European Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Yao et al., 2016] Yuan Yao, Brian Logan, and John Thangarajah. Robust execution of BDI agent programs by exploiting synergies between intentions. In 30th AAAI Conference on Artificial Intelligence, pages 2558-2565. AAAI Press, 2016.","title":"Robust execution of BDI agent programs by exploiting synergies between intentions","authors":"Yuan Yao, Brian Logan, John Thangarajah","year":"2016","venue":"30th AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}