BDI Agents: From Theory to Practice

By Anand Srinivasa Rao, M. Georgeff. 1995

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Citations in the corpus

Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences (2017, background): “…doing deliberative reasoning, and the concepts used in his work are closely linked to that of systems such as belief-desire-intention models [Rao and Georgeﬀ, 1995] However, simulating an entire causal chain is in-feasible in most cases, so cognitive scientists and social psychologists have…”
Plan explicability and predictability for robot task planning (2015, background): “For example, to darken a room that is too bright, a robot can either adjust the window blinds, switch off the lights, or break the light bulbs in the room.”
Developing multi‐agent systems with a FIPA‐compliant agent framework (2001, background): “In this period, there is a lot of activity concerning the development of agent systems (see, for example, DMARS [7], RETSINA [8] and MOLE [9]), and the standardization of these systems, where in the past KSE [10], OMG [11] and then FIPA [12] led the activity.”
Situation awareness-based agent transparency and human-autonomy teaming effectiveness (2018, background): “Chen and associates (2014) leveraged Endsley ’ s model of SA (Endsley 1995), the BDI (Beliefs, Desires, Intentions) Agent Framework (Rao and Georgeff 1995), Lee ’ s 3Ps described above (2012), and other relevant previous work (Chen and Barnes 2012a, Chen and Barnes 2012b; Lyons and Havig 2014) to…”
Situation Awareness-Based Agent Transparency (2014, unknown): “…the SA-based Agent Transparency (SAT) (figure 1), based on the theory of SA (Endsley, 1995), the Beliefs, Desires, Intentions (BDI) Agent Framework (Rao and Georgeff, 1995), Lee’s 3Ps described previously (Lee, 2012), and other relevant previous work (Chen and Barnes, 2012a, 2012b; Chen and…”
Human–Agent Teaming for Multirobot Control: A Review of Human Factors Issues (2014, methodology): “The BDI framework has been used to develop mixedinitiative systems in various contexts, where agents’ beliefs are updated based on their perception of the environment, communications with other agents/humans, and their inference mechanisms [41], [76], [77].”
Agent-Oriented Software Engineering: The State of the Art (2009, background): “Two of the best known such logical frameworks are the Cohen-Levesque theory of intention [14], and the Rao-Georgeff belief-desire-intention model [60, 74].”
Multiagent Systems: A Survey from a Machine Learning Perspective (2000, methodology): “One example is Rao and Georgeff’s OASIS system (see Section 8) which reas ons about when to be reactive and when to follow goal-directed plans [16].”
JADE: A software framework for developing multi-agent applications. Lessons learned (2008, methodology): “That means users do no need either to understand or use any BDI architecture , architecture which exists in litera - ture in hundreds of flavours and that has not yet gained acceptance in the software engineering community .”
Algorithms for the Greater Good! On Mental Modeling and Acceptable Symbiosis in Human-AI Collaboration (2018, methodology): “Classical AI models such as STRIPS (Fikes and Nilsson 1971) and BDI (Rao, Georgeff, and others 1995) models were, in fact, largely built out of theories in folk psychology (Malle 2004).”
A Canonical Theory of Dynamic Decision-Making (2012, background): “Such “BDI agents” have proved to be a practical basis for designing software agents (e.g., Rao and Georgeff, 1995).”
Jadex: A BDI Reasoning Engine (2005, unknown): “The BDI theory of Rao and Georgeﬀ [28] deﬁnes beliefs, desires, and intentions as mental attitudes represented as possible world states.”
A Survey of Trust and Reputation Management Systems in Wireless Communications (2010, methodology): “Based on the belief–desire–intention (BDI) model [4] of agent mental state modeling, they take a cognitive”