High-performing human teams leverage intelligent and efficient communication coordination strategies to collaboratively maximize their joint utility. Inspired by teaming behaviors among humans, I seek develop computational methods for synthesizing collaborative multi-robot systems. both classical model-based control planning approaches as well data-driven such Multi-Agent Reinforcement Learning...

Unlike traditional machine learning methods, humans often learn from natural language instruction. As users become increasingly accustomed to interacting with mobile devices using speech, their interest in instructing these devices in natural language is likely to grow. We introduce our Learning by Instruction Agent (LIA), an intelligent personal agent that users can teach to perform new action...

Hongbo Lan, Chengrui Zhang, Riliang Liu School of Mechanical Engineering, Shandong University, Jinan, 250061, China School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, 710049, China Abstract This paper presents a conceptual framework of STEP-NP controller to implement intelligent control for CNC machine tool. This framework is developed based on the concept of multi-agent system...

Agent-based economy or agent-based electronic commerce is the term for describing one of possible next steps of electronic commerce. The systematic understanding of the agent-based economy is important for researchers to develop practical intelligent agent systems, and for current electronic commerce industries to cope with the challenges of the intelligent agents. With these purposes, we condu...

The paper discusses a study on the application of intelligent agents (IAs) to conceptual designing. It provides an overview of the state-of-the-art in the areas of ontologies and IAs. Next, the system Disciple, a learning intelligent agent shell, and system Inventor 2001, evolutionary design support tool, both developed at George Mason University, are briefly presented. Further, the paper intro...

This paper addresses collaborative learning in the medical domain, focusing on the evaluation of a component specially devised to promote collaborative learning using the AMPLIA system. AMPLIA is an intelligent multi-agent environment that supports diagnostic reasoning and the modeling of diagnostic hypotheses in the medical domain. Recently it has been extended with a new component providing a...

This paper addresses collaborative learning in the medical domain. In particular, it focuses on the evaluation of a component specially devised to promote collaborative learning using AMPLIA. AMPLIA is an intelligent multi-agent environment to support diagnostic reasoning and the modeling of diagnostic hypotheses in domains with complex and uncertain knowledge, such as the medical domain. Recen...