A major challenge within open markets is the ability to satisfy service demand with an adequate supply of service providers, especially when such demand may be volatile due to cha...
Mariusz Jacyno, Seth Bullock, Michael Luck, Terry ...
In this paper we address the problem of decentralised coordination for agents that must make coordinated decisions over continuously valued control parameters (as is required in m...
Ruben Stranders, Alessandro Farinelli, Alex Rogers...
This paper addresses decentralized multi-project scheduling under uncertainty. The problem instance we study is the scheduling of airport ground handling services, where aircraft ...
Experimental analysis of agent strategies in multiagent systems presents a tradeoff between granularity and statistical confidence. Collecting a large amount of data about each s...
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
We study combinatorial prediction markets where agents bet on the sum of values at any tree node in a hierarchy of events, for example the sum of page views among all the children...
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
In context-aware route planning, a set of agents has to plan routes on a common infrastructure and each agent has to plan a conflict-free route from a source to a destination wit...
Adriaan ter Mors, Jeroen van Belle, Cees Witteveen
Distributed constraint optimization (DCOP) provides a framework for coordinated decision making by a team of agents. Often, during the decision making, capacity constraints on age...