Constrained multiagent Markov decision processes: A taxonomy of problems and algorithms

In domains such as electric vehicle charging, smart distribution grids and autonomous warehouses, multiple agents share the same resources. When planning the use of these resources, agents need to deal with the uncertainty in these domains. Although several models and algorithms for such constrained multiagent planning problems under...

Resource-constrained Multi-agent Markov Decision Processes

Intelligent autonomous agents, designed to automate and simplify many aspects of our society, will increasingly be required to also interact with other agents autonomously. Where agents interact, they are likely to encounter resource constraints. For example, agents managing household appliances to optimize electricity usage might need to share...

Multi-agent Planning Under Uncertainty for Capacity Management

Demand response refers to the concept that power consumption should aim to match supply, instead of supply following demand. It is a key technology to enable the successful transition to an electricity system that incorporates more and more intermittent and uncontrollable renewable energy sources. For instance, loads such as heat pumps or...

Capacity-aware Sequential Recommendations

Personalized recommendations are increasingly important to engage users and guide them through large systems, for example when recommending points of interest to tourists visiting a popular city. To maximize long-term user experience, the system should consider issuing recommendations sequentially, since by observing the user's response to a...

Preallocation and Planning under Stochastic Resource Constraints

Resource constraints frequently complicate multi-agent planning problems. Existing algorithms for resource-constrained, multi-agent planning problems rely on the assumption that the constraints are deterministic. However, frequently resource constraints are themselves subject to uncertainty from external influences. Uncertainty about constraints...

Bounding the probability of resource constraint violations in multi-agent MDPs

Multi-agent planning problems with constraints on global resource consumption occur in several domains. Existing algorithms for solving Multi-agent Markov Decision Processes can compute policies that meet a resource constraint in expectation, but these policies provide no guarantees on the probability that a resource constraint violation will...

Decoupling a Resource Constraint through Fictitious Play in Multi-agent Sequential Decision Making

When multiple independent agents use a limited shared resource, they need to coordinate and thereby their planning problems become coupled. We present a resource assignment strategy that decouples agents using marginal utility cost, allowing them to plan individually. We show that agents converge to an expected cost curve by keeping a history of...

Evaluation and Improvement of Laruelle-Widgrén Inverse Banzhaf Approximation

Voting is a popular way of reaching decisions in multi-agent systems. Weighted voting in particular allows different agents to have varying levels of influence on the decision taken: each agent’s vote carries a weight, and a proposal is accepted if the sum of the weights of the agents in favor of the proposal is at least equal to a given quota....