ChatterBots, TinyMuds, and the Turing test: entering the Loebner Prize competition
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Entertaining agents: a sociological case study
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Team-partitioned, opaque-transition reinforcement learning
Proceedings of the third annual conference on Autonomous Agents
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Cobot in LambdaMOO: A Social Statistics Agent
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
CobotDS: a spoken dialogue system for chat
Eighteenth national conference on Artificial intelligence
User modeling for personalized universal appliance interaction
Proceedings of the 2003 conference on Diversity in computing
Optimizing the mutual intelligibility of linguistic agents in a shared world
Artificial Intelligence
From devices to tasks: automatic task prediction for personalized appliance control
Personal and Ubiquitous Computing
Teaching virtual characters how to use body language
Lecture Notes in Computer Science
Comparing end-user and intelligent remote control interface generation
Personal and Ubiquitous Computing
Experiments in socially guided machine learning: understanding how humans teach
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
A globally optimal algorithm for TTD-MDPs
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Teachable robots: Understanding human teaching behavior to build more effective robot learners
Artificial Intelligence
Learning polite behavior with situation models
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
How people talk when teaching a robot
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
Targeting specific distributions of trajectories in MDPs
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Learning policies for embodied virtual agents through demonstration
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Exploiting social partners in robot learning
Autonomous Robots
Emotion and reinforcement: affective facial expressions facilitate robot learning
ICMI'06/IJCAI'07 Proceedings of the ICMI 2006 and IJCAI 2007 international conference on Artifical intelligence for human computing
A behavior adaptation method for an elderly companion robot: Rui
ICSR'10 Proceedings of the Second international conference on Social robotics
Teachable characters: user studies, design principles, and learning performance
IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
Exploiting user feedback for adapting mobile interaction obtrusiveness
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
Shared control of a robot using EEG-based feedback signals
Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication
Triggering effective social support for online groups
ACM Transactions on Interactive Intelligent Systems (TiiS)
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We report on our reinforcement learning work on Cobot, a software agent that resides in the well-known online chat community LambdaMOO. Our initial work on Cobot~\cite{cobotaaai} provided him with the ability to collect {\em social statistics\/} and report them to users in a reactive manner. Here we describe our application of reinforcement learning to allow Cobot to proactively take actions in this complex social environment, and adapt his behavior from multiple sources of human reward. After 5 months of training, Cobot received 3171 reward and punishment events from 254 different Lambda\-MOO users, and learned nontrivial preferences for a number of users. Cobot modifies his behavior based on his current state in an attempt to maximize reward. Here we describe LambdaMOO and the state and action spaces of Cobot, and report the statistical results of the learning experiment.