Computational Approaches for Stochastic Shortest Path on Succinct MDPs

We consider the stochastic shortest path (SSP) problem for succinct Markov decision processes (MDPs), where the MDP consists of a set of variables, and a set of nondeterministic rules that update the variables. First, we show that several examples from the AI literature can be modeled as succinct MDPs. Then we present computational approaches for upper and lower bounds for the SSP problem: (a)~for computing upper bounds, our method is polynomial-time in the implicit description of the MDP; (b)~for lower bounds, we present a polynomial-time (in the size of the implicit description) reduction to quadratic programming. Our approach is applicable even to infinite-state MDPs. Finally, we present experimental results to demonstrate the effectiveness of our approach on several classical examples from the AI literature

Autonomous Agents and Multiagent Systems [electronic resource] : AAMAS 2017 Workshops, Best Papers, São Paulo, Brazil, May 8-12, 2017, Revised Selected Papers /

This book features a selection of best papers from 13 workshops held at the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017.  The 17 full papers presented in this volume were carefully reviewed and selected for inclusion in this volume. They cover specific topics, both theoretical and applied, in the general area of autonomous agents and multiagent systems. .Elastic and Load-spike Proof One-to-many Negotiation to Improve The Service Acceptability of an Open SaaS Provider -- Opponent Modeling with Information Adaptation (OMIA) in Automated Negotiations -- Uncertainty Assessment in Agent-Based Simulation: An Exploratory Study -- Developing multi-agent-based thought experiments: a case study on the evolution of gamete dimorphism.-Cooperative Multi-Agent Control Using Deep Reinforcement Learning -- Stereotype Reputation with Limited Observability -- Working Together: Committee Selection and the Supermodular Degree -- On the Deployment of Factor Graph Elements to Operate Max-Sum in Dynamic Ambient Environments -- Optimizing Peer Teaching to Enhance Team Performance -- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections -- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.-Convention Emergence in Partially Observable Topologies.-Reasoning about Opportunistic Propensity in Multi-agent Systems -- Approaching Interactions in Agent-Based Modelling with an Affordance Perspective.-Towards a fast detection of opponents in repeated stochastic game -- Event Calculus agent minds applied to diabetes monitoring -- Multiple-Profile Prediction-of-Use Games. .This book features a selection of best papers from 13 workshops held at the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017.  The 17 full papers presented in this volume were carefully reviewed and selected for inclusion in this volume. They cover specific topics, both theoretical and applied, in the general area of autonomous agents and multiagent systems.