A Roadmap of Agent Research and Development
By Nicholas R. Jennings, Katia P. Sycara, Michael J. Wooldridge. Autonomous Agents and Multi-Agent Systems, 2004
2,370 citations recorded by the source corpus.
This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.
Subfields: Artificial Intelligence, Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/470faf8f81f4bfffc9982f8d3fc57abf05b16840
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Kagan Tumer
- Adrian K. Agogino
- David Hilton Wolpert
- Shuyan Zhou
- Katia P. Sycara
- Massimo Paolucci
- Nigel R. Shadbolt
- Juan C. García-Ojeda
In Computer Networks and Communications
- Katia P. Sycara
- Massimo Paolucci
- Nigel R. Shadbolt
- Juan C. García-Ojeda
- Dipti Srinivasan
- Nicholas R. Jennings
- Graham Neubig
- Scott A. DeLoach
Citations in the corpus
- Smart sensing technology: opportunities and challenges (2004, neutral): “programming, and concurrent object-based systems, as well as human-computer interface design ( Jennings, et al. 1998 ).”
- Learning sequences of actions in collectives of autonomous agents (2002, background): “Addressing these two issues simultaneously is one of the main problems in designing multi-agent systems [9, 12].”
- VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks (2024, background): “Automating routine computer tasks with autonomous agents is a long standing goal of artificial intelligence research (Franklin & Graesser, 1996; Jennings et al., 1998).”
- The Next Generation of Research on IS Use: A Theoretical Framework of Delegation to and from Agentic IS Artifacts (2021, background): “To elaborate, a rational software-based agent is “a computer system, situated in some environment, that is capable of flexible autonomous action in order to meet its design objectives” (Jennings et al. 1998, p. 276).”
- A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments (2003, background): “This accords with the view that agents are action-based systems that can autonomously act upon the environment and/or interact with other agents [21].”
- Self-Organisation: Paradigms and Applications (2003, background): “A software agent may understand a user's request through a user's interface, and send an e-mail to the user once the request has been satisfied [46] [32].”
- The RETSINA MAS Infrastructure (2003, background): “We claim that the MAS infrastructure should be general enough to support various coordination schemes such as team behavior (Tambe, 1997), negotiation (Jennings et al., 1998; Sycara, 1990), Contract Nets (Smith, 1980) etc.”
- An Introduction to Multi-Agent Systems (2010, background): “Distributed artificial intelligence (DAI) is a subfield of Artificial Intelligence [1] that has gained considerable importance due to its ability to solve complex real-world problems.”
- O-MaSE: a customisable approach to designing and building complex, adaptive multi-agent systems (2010, background): “Jennings et al. (1998) mention two major obstacles to widespread adoption of agent technologies in industry: 1 the lack of complete methodologies and processes to help designers to specify, analyse, and design agent-based applications 2 the lack of industrial-strength agent-based toolkits.”
- Research, part of a Special Feature on Empirical based agent-based modeling Agent-based Analysis of Agricultural Policies: an Illustration of the Agricultural Policy Simulator AgriPoliS, its Adaptation and Behavior (2006, background): “…Simulator (AgriPoliS) is the understanding and modeling of an agricultural system as an agent-based system (Russel and Norvig 1995, Franklin and Graesser 1997, Jennings et al. 1998, Ferber 1999, Gilbert and Troitzsch 1999, Luck et al. 2003, Parker et al. 2003, Tesfatsion, unpublished manuscript).”
- A Survey of Collectives (2004, background): “The associated design steps involve [121]:”