多智能体系统
Deception is virtually ubiquitous in warfare, and should be a central consideration for military operations research. However, studies of agent behaviour in simulated operations have typically neglected to include explicit models of…
Mobile wireless sensors are increasingly recognized as a valuable tool for monitoring critical infrastructures. An important use case is the discovery of leaks and inflows in pipe networks using a swarm of floating sensor nodes. While…
Cooperation in multi-agent and multi-robot systems can help agents build various formations, shapes, and patterns presenting corresponding functions and purposes adapting to different situations. Relationships between agents such as their…
We describe ACE0, a lightweight platform for evaluating the suitability and viability of AI methods for behaviour discovery in multiagent simulations. Specifically, ACE0 was designed to explore AI methods for multi-agent simulations used in…
Social dilemmas have been widely studied to explain how humans are able to cooperate in society. Considerable effort has been invested in designing artificial agents for social dilemmas that incorporate explicit agent motivations that are…
In task allocation for real-time domains, such as disaster response, a limited number of agents is deployed across a large area to carry out numerous tasks, each with its prerequisites, profit, time window and workload. To maximize profits…
One practical requirement in solving dynamic games is to ensure that the players play well from any decision point onward. To satisfy this requirement, existing efforts focus on equilibrium refinement, but the scalability and applicability…
A model of interacting agents, following plausible behavioral rules into a world where the Covid-19 epidemic is affecting the actions of everyone. The model works with (i) infected agents categorized as symptomatic or asymptomatic and (ii)…
Distributed artificial intelligence (DAI) studies artificial intelligence entities working together to reason, plan, solve problems, organize behaviors and strategies, make collective decisions and learn. This Ph.D. research proposes a…
In this paper, we propose the integration of approaches to Engineering Multi-Agent Systems (EMAS) with the Developer Operations (DevOps) industry best practice. Whilst DevOps facilitates the organizational autonomy of software teams, as…
We propose a decentralized game-theoretic framework for dynamic task allocation problems for multi-agent systems. In our problem formulation, the agents' utilities depend on both the rewards and the costs associated with the successful…
We consider the challenging problem of tracking multiple objects using a distributed network of sensors. In the practical setting of nodes with limited field of views (FoVs), computing power and communication resources, we develop a novel…
Calibration is an essential process to make an agent-based simulator operational. Especially, the calibration for freight demand is challenging due to the model complexity and the shortage of available freight demand data compared with…
Violence against women occurs predominantly in the family and domestic context. The COVID-19 pandemic led Brazil to recommend and, at times, impose social distancing, with the partial closure of economic activities, schools, and…
Network slicing (NS) management devotes to providing various services to meet distinct requirements over the same physical communication infrastructure and allocating resources on demands. Considering a dense cellular network scenario that…
In recent years, Unmanned Aerial Vehicles (UAVs) have been used in fields such as architecture, business delivery, military and civilian theaters, and many others. With increased applications comes the increased demand for advanced…
Pursuit-evasion is the problem of capturing mobile targets with one or more pursuers. We use deep reinforcement learning for pursuing an omni-directional target with multiple, homogeneous agents that are subject to unicycle kinematic…
Recently, a detailed epistemic reasoning framework for multi-agent systems with byzantine faulty asynchronous agents and possibly unreliable communication was introduced. We have developed a modular extension framework implemented on top of…
The communication topology is an essential aspect in designing distributed optimization heuristics. It can influence the exploration and exploitation of the search space and thus the optimization performance in terms of solution quality,…
Underlying relationships among multi-agent systems (MAS) in hazardous scenarios can be represented as Game-theoretic models. We measure the performance of MAS achieving tasks from the perspective of balancing success probability and system…