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- 30Reinforcement learning
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- 12Reinforcement Learning
- 9Planning
- 7Computer Games
- 4Müller, Martin
- 3Mueller, Martin
- 2Bowling, Michael
- 2Johanson, Michael
- 2Mahmood, Ashique
- 2Nakhost, Hootan
- 72Graduate and Postdoctoral Studies (GPS), Faculty of
- 72Graduate and Postdoctoral Studies (GPS), Faculty of /Theses and Dissertations
- 20Computing Science, Department of
- 20Computing Science, Department of/Technical Reports (Computing Science)
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2017-12-01
Jeff Cho, Shelby Carleton, Aidan Herron, Maddy Hebert, Brandon Wieliczko, Kieran Downs
turing is a text adventure-style game created in RenPy using a custom-built text adventure engine. In this game, you play as a new employee of the mysterious Electric Sheep Inc. screening “candidates” through a chat interface to determine whether they are human or AI. Your interface to this...
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[Review of the book Formal Methods in Artificial Intelligence, by Aamsay]
1996
Introduction: Many universities teach artificial intelligence (AI) by having one undergraduate course that introduces students to a very wide variety of topics, usually including search and search heuristics, representational systems (including formal logic), problem solving, vision, expert...
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1991
Pelletier, Francis J., Schubert, Lenhart
Introduction: This very short book is apparently intended as a supplementary text in a graduate AI course. The author describes it as a \"text and reference work on the applications of non-standard logics to artificial intelligence (AI).\" It gives short and concise (too short and too concise, in...
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Spring 2012
Mirian HosseinAbadi, MahdiehSadat
In this thesis we propose a computational model of animal behavior in spatial navigation, based on reinforcement learning ideas. In the field of computer science and specifically artificial intelligence, replay refers to retrieving and reprocessing the experiences that are stored in an abstract...
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Fall 2015
Brammadesam Manavalan, Yathirajan
Displaying believable emotional reactions in virtual characters is required in applications ranging from virtual-reality trainers to video games. Manual scripting is the most frequently used method and enables an arbitrarily high fidelity of the emotions displayed. However, scripting is labor...
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2010
Lin, Guohui, Shi, Xiaoyu, Hu, Yu, Zeng, Dahua, Zaiane, Osmar
Technical report TR10-04. This paper describes a novel and fast placement algorithm for field programmable gate array (FPGA) design space exploration. The proposed algorithm generates the placement based on the topological similarity between two configurations (netlists) in the design space....
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Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement - Extended Version
Download2010
Nakhost, Hootan, Müller, Martin
Technical report TR10-01. Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become increasingly important. The most recent planning competition IPC-2008 used the cost of the...
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Spring 2021
Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the environmental reward, appears to improve both exploration and representation learning. The question we tackle in this...
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Adaptive and Autonomous Switching: Shared Control of Powered Prosthetic Arms Using Reinforcement Learning
DownloadFall 2016
Powered prosthetic arms with numerous controllable functions (i.e., grip patterns or movable joints) can be challenging to operate. Gated control---a common control method for myoelectric arms and other human-machine interfaces---allows users to select a function by switching through a static...
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2013
Sturtevant, Nathan R., Valenzano, Richard, Schaeffer, Jonathan
While greedy best-first search (GBFS) is a popular algorithm for solving automated planning tasks, it can exhibit poor performance if the heuristic in use mistakenly identifies a region of the search space as promising. In such cases, the way the algorithm greedily trusts the heuristic can cause...