Large-Scale Wildfire Mitigation Through Deep Reinforcement Learning

Forest management can be seen as a sequential decision-making problem to determine an optimal scheduling policy, e.g., harvest, thinning, or do-nothing, that can mitigate the risks of wildfire. Markov Decision Processes (MDPs) offer an efficient mathematical framework for optimizing forest management policies. However, computing optimal MDP...

Infrastructure maintenance and replacement optimization under multiple uncertainties and managerial flexibility

Infrastructure maintenance and replacement decisions are subject to uncertainties such as regular asset degradation, structural failure, and price uncertainty. In the engineering domain, Markov Decision Processes (MDPs) typically focus on uncertainties regarding asset degradation and structural failure. While the literature in the engineering...

Improving mobile video quality through predictive channel quality based buffering

Frequent variations in throughput make mobile networks a challenging environment for video streaming. Current video players deal with those variations by matching video quality to network throughput. However, this adaptation strategy results in frequent changes of video resolution and bitrate, which negatively impacts the users' streaming...

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...

Solving Transition-Independent Multi-agent MDPs with Sparse Interactions

In cooperative multi-agent sequential decision making under uncertainty, agents must coordinate to find an optimal joint policy that maximises joint value. Typical algorithms exploit additive structure in the value function, but in the fully-observable multi-agent MDP (MMDP) setting such structure is not present. We propose a new optimal solver...