Assisting Persons with Dementia during Handwashing Using a Partially Observable Markov Decision Process Jesse Hoey1 , Axel von Bertoldi2 , Pascal Poupart3 , and Alex Mihailidis2 1

Source URL: cs.uwaterloo.ca

EE365: Markov Decision Problems Markov decision process Markov decision problem Examples

Source URL: www.nicholasmoehle.com

Mutual State-Based Capabilities for Role Assignment in Heterogeneous Teams Somchaya Liemhetcharat Manuela Veloso

Source URL: somchaya.org

• Probability theory
• Probability
• Statistics
• Robot
• Algorithm
• Expected value
• Variance
• Ethics
• Markov decision process
• Swarm behaviour

Online Development of Assistive Robot Behaviors for Collaborative Manipulation and Human-Robot Teamwork Bradley Hayes and Brian Scassellati Yale University Computer Science Department New Haven, CT 06511

Source URL: bradhayes.info

• Artificial intelligence
• Robotics
• Dynamic programming
• Markov processes
• Stochastic control
• Machine learning
• Probability theory
• Probability
• Partially observable Markov decision process
• Humanoid robot
• Reinforcement learning
• Humanrobot interaction

I N F S Y S R E S E A R C H R

Source URL: www.kr.tuwien.ac.at

• Artificial intelligence
• Logic programming
• Academia
• Decision theory
• Game theory
• Non-cooperative games
• Situation calculus
• Nash equilibrium
• Zero-sum game
• Markov decision process
• Strategy
• Mathematical optimization

IFAAMAS Board Elections 2016 Statement Bio Matthijs Spaan is an assistant professor of Computer Science at Delft University of Technology, the Netherlands. He holds a PhD degree in Computer Scienceand an MSc degr

Source URL: www.aamas-conference.org

• Artificial intelligence
• Systems science
• Academia
• International Conference on Autonomous Agents and Multiagent Systems
• Reinforcement learning
• International Joint Conference on Artificial Intelligence
• Agent-based model
• Partially observable Markov decision process
• Multi-agent system
• Intelligent agent
• Peter Stone

Chapter 1 Introduction The idea that we learn by interacting with our environment is probably the first to occur to us when we think about the nature of learning. When an infant plays, waves its arms, or looks about, it

Source URL: webdocs.cs.ualberta.ca

• Cognition
• Psychology
• Academia
• Behaviorism
• Educational psychology
• Belief revision
• Reinforcement learning
• Computational neuroscience
• Reinforcement
• Markov decision process
• Machine learning
• Learning

From FOND to Probabilistic Planning: Guiding search for quality policies Alberto Camacho† , Christian Muise∗ , Akshay Ganeshen† , Sheila A. McIlraith† † Department of Computer Science, University of Toronto Dep

Source URL: www.haz.ca

• Probability
• Amyloidosis
• Logic
• Formal epistemology
• Non-classical logic
• Probabilistic logic
• Automated planning and scheduling
• PRNP
• Markov decision process
• Planning Domain Definition Language
• PP

Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling Goal-Based Action Priors David Abel, D. Ellis Hershkowitz, Gabriel Barth-Maron, Stephen Brawner, Kevin O’Farrell, James Mac

Source URL: h2r.cs.brown.edu

• Cognitive science
• Artificial intelligence
• Automated planning and scheduling
• Probability
• Dynamic programming
• Markov processes
• Stochastic control
• Reinforcement learning
• Markov decision process
• Motion planning
• Action selection
• Prior probability

Social Hierarchical Learning: Enabling Human-Robot Teaming Bradley Hayes Dept. of Computer Science,Yale University Human-robot teaming has the potential to enable robots to perform well beyond

Source URL: bradhayes.info

• Automated planning and scheduling
• Hierarchical task network
• Partially observable Markov decision process
• Robotics
• Robot
• Windows Task Scheduler
• Probability theory
• Software
• Computing