Výsledky vyhledávání

Report

Towards a Better Understanding of Learning with Multiagent Teams

Autor: Radke, David, Larson, Kate, Brecht, Tim, Tilbury, Kyle

While it has long been recognized that a team of individual learning agents can be greater than the sum of its parts, recent work has shown that larger teams are not necessarily more effective than smaller ones. In this paper, we study why and under

Externí odkaz: http://arxiv.org/abs/2306.16205

Zobrazit plný text záznamu

Report

Exploring the Benefits of Teams in Multiagent Learning

Autor: Radke, David, Larson, Kate, Brecht, Tim

For problems requiring cooperation, many multiagent systems implement solutions among either individual agents or across an entire population towards a common goal. Multiagent teams are primarily studied when in conflict; however, organizational psyc

Externí odkaz: http://arxiv.org/abs/2205.02328

Zobrazit plný text záznamu

Report

The Importance of Credo in Multiagent Learning

Autor: Radke, David, Larson, Kate, Brecht, Tim

We propose a model for multi-objective optimization, a credo, for agents in a system that are configured into multiple groups (i.e., teams). Our model of credo regulates how agents optimize their behavior for the groups they belong to. We evaluate cr

Externí odkaz: http://arxiv.org/abs/2204.07471

Zobrazit plný text záznamu

Report

CAN Radar: Sensing Physical Devices in CAN Networks based on Time Domain Reflectometry

Autor: Rumez, Marcel, Dürrwang, Jürgen, Brecht, Tim, Steinshorn, Timo, Neugebauer, Peter, Kriesten, Reiner, Sax, Eric

The presence of security vulnerabilities in automotive networks has already been shown by various publications in recent years. Due to the specification of the Controller Area Network (CAN) as a broadcast medium without security mechanisms, attackers

Externí odkaz: http://arxiv.org/abs/1910.02847

Zobrazit plný text záznamu