Designing "teams of intelligent agents that successfully coordinate and learn about their complex environments inhabited by other agents (such as humans)" is one of the major goals of AI, and it is the challenge that I aim to address in my research. In this paper I give an overview of some of the foundations, insights and challenges in this field of Interactive Learning and Decision Making
This paper proposes a research direction to advance AI which draws inspiration from cognitive theori...
We study how humans make decisions when they collaborate with an artificial intelligence (AI) in a s...
Abstract. Human-AgentInteraction as a speci c area of Human-Computer Interaction is of primary impor...
Designing "teams of intelligent agents that successfully coordinate and learn about their complex en...
This book describes interactive learning environments (ILEs) and their underlying concepts. It expla...
Over the past few years, artificial intelligence (AI) has achieved great success in a variety of app...
We present results and research projects about the computational aspects of classical problems in Ar...
This chapter deals with three key issues related to designing and building intelligent agents. First...
The ability to learn is essential to intelligent agents that need to adapt to dynamic, non-determini...
In this position paper, we analyze ways that a human can best be involved in interactive artificial ...
Multiagent systems is an expanding field that blends classical fields like game theory and decentral...
AbstractThe area of learning in multi-agent systems is today one of the most fertile grounds for int...
Decision-making is a complex process that involves data that is derived based on set of rules. Conve...
Accés lliure al text del llibre a la web de l'editorKnowledge, reasoning and learning (KRL) play a c...
The premise of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making is th...
This paper proposes a research direction to advance AI which draws inspiration from cognitive theori...
We study how humans make decisions when they collaborate with an artificial intelligence (AI) in a s...
Abstract. Human-AgentInteraction as a speci c area of Human-Computer Interaction is of primary impor...
Designing "teams of intelligent agents that successfully coordinate and learn about their complex en...
This book describes interactive learning environments (ILEs) and their underlying concepts. It expla...
Over the past few years, artificial intelligence (AI) has achieved great success in a variety of app...
We present results and research projects about the computational aspects of classical problems in Ar...
This chapter deals with three key issues related to designing and building intelligent agents. First...
The ability to learn is essential to intelligent agents that need to adapt to dynamic, non-determini...
In this position paper, we analyze ways that a human can best be involved in interactive artificial ...
Multiagent systems is an expanding field that blends classical fields like game theory and decentral...
AbstractThe area of learning in multi-agent systems is today one of the most fertile grounds for int...
Decision-making is a complex process that involves data that is derived based on set of rules. Conve...
Accés lliure al text del llibre a la web de l'editorKnowledge, reasoning and learning (KRL) play a c...
The premise of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making is th...
This paper proposes a research direction to advance AI which draws inspiration from cognitive theori...
We study how humans make decisions when they collaborate with an artificial intelligence (AI) in a s...
Abstract. Human-AgentInteraction as a speci c area of Human-Computer Interaction is of primary impor...