MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-Based Residential Demand Response

This paper presents a decentralized Multi-Agent Reinforcement Learning (MARL) approach to an incentive-based Demand Response (DR) program, which aims to maintain the capacity limits of the electricity grid and prevent grid congestion by financially incentivizing residential consumers to reduce their energy consumption. The proposed approach...

MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response

Distribution System Operators (DSOs) are responsible preventing grid congestion, while accounting for growing demand and the intermittent nature of renewable energy resources. Incentive-based demand response programs promise real-time flexibility to relieve grid congestion. To include residential consumers in these programs, aggregators can...

Multi-­Robot Exploration and Planning in Limited Communication Environments

Distributed cooperative robots can be highly beneficial in mapping disaster environments and assisting with search and rescue operations. In most situations such environments only allow for only limited communication between robots. This thesis reports on simulation experiments conducted to test the impact of having only partial communication...

Network-Decentralized Simultaneous Localization and Mapping by Multi-Agent Systems

Multi-Agent Systems (MAS) can be used in the exploration and mapping of unknown environments. To cooperate autonomously, each agent of the MAS must know its own location precisely within such an environment. Simultaneous Localization and Mapping (SLAM) techniques are commonly used when the Global Positioning System (GPS) is unavailable or does...

Agent-Based Distributed Planning and Coordination for Resilient Airport Surface Movement Operations

Airport surface movement operations are complex systems that experience many types of adverse events which require resilient, safe and efficient responses. One regularly occurring adverse event is that of runway reconfigurations. Agent based distributed planning and coordination has shown promising results in controlling and maintaining...

Adaptive Synchronization over Uncertain Multi-Agent Systems: A distributed homogenization-based approach

A challenging task in synchronization of multi-agent systems is steering the network towards a coherent solution when the dynamics of the constituent systems are heterogeneous and residing in a possibly large uncertainty set. In this situation, synchronization can be achieved via adaptive protocols (with adaptive feedback gains, or adaptive...

Performance of Strategies for the Iterated Prisoner’s Dilemma in a Natural Environment

In nature, all species have their own behaviors and strategies for survival. Some species survive and reproduce, while others become extinct. This paper proposes a model to simulate these strategies and test their performance. Natural behavior is represented as strategies for the iterated Prisoner's Dilemma (IPD). Agents wielding one of ten...

Synchronization of Uncertain Heterogeneous Agents: An Adaptive Virtual Model Reference Approach

Synchronization of Multi-Agent Systems (MASs) has the potential to benefit many technological<br/>areas such as formation control for unmanned vehicles, cooperative adaptive<br/>cruise control, and spacecraft attitude control. Information plays a crucial role in MASs:<br/>in centralized approaches, a central node utilizes global information to...