2019.06.02 Multiagent papers

 

05-29-2019

Anti-efficient encoding in emergent communication
by Rahma Chaabouni et al

05-28-2019

Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning
by Shariq Iqbal et al

05-28-2019

Heuristics in Multi-Winner Approval Voting
by Jaelle Scheuerman et al

05-28-2019

A Parameterized Perspective on Protecting Elections
by Palash Dey et al

05-29-2019

Modeling Theory of Mind in Multi-Agent Games Using Adaptive Feedback Control
by Ismael T. Freire et al

05-29-2019

Scalable and transferable learning of algorithms via graph embedding for multi-robot reward collection
by Hyunwook Kang et al

05-31-2019

Attentional Policies for Cross-Context Multi-Agent Reinforcement Learning
by Matthew A. Wright et al

05-29-2019

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing
by Oscar J. Romero

05-28-2019

Miss Tools and Mr Fruit: Emergent communication in agents learning about object affordances
by Diane Bouchacourt et al

05-30-2019

A Value-based Trust Assessment Model for Multi-agent Systems
by Kinzang Chhogyal et al

05-29-2019

Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks
by Gabriele Farina et al

05-30-2019

Ridesharing with Driver Location Preferences
by Duncan Rheingans-Yoo et al

05-28-2019

Justification Based Reasoning in Dynamic Conflict Resolution
by Werner Damm et al

05-29-2019

Robo-Taxi service fleet sizing: assessing the impact of user trust and willingness-to-use
by Reza Vosooghi et al

05-28-2019

AsymDPOP: Complete Inference for Asymmetric Distributed Constraint Optimization Problems
by Yanchen Deng et al

05-30-2019

New Algorithms for Functional Distributed Constraint Optimization Problems
by Khoi D. Hoang et al

05-30-2019

An Introduction to Engineering Multiagent Industrial Symbiosis Systems: Potentials and Challenges
by Vahid Yazdanpanah et al

05-28-2019

CARE: Cooperative Autonomy for Resilience and Efficiency of Robot Teams for Complete Coverage of Unknown Environments under Robot Failures
by Junnan Song et al

 
Craig Smith