Procedural Agent Model for Plan Recognition
نویسنده
چکیده
We propose a formal procedure-based agent model for plan recognition as an alternative to the declarative proposition-based agent model. Our formalism, called the Procedural Agent Model (PAM) allows us to describe procedural plans of agents in a concise and abstract way. Plan recognition uses PAM as a library of plan schemas and applies a graph-based pattern-matching algorithm to the observed events to nd a matching PAM. The associated intentions can then be inferred from the goals of matching PAM. We are also investigating the extension of our PAM representation to a prob-abilistic procedural agent model by incorporating uncertainty in observation and probabilistic state transition.
منابع مشابه
IJCAI ’ 95 Workshop on the Next Generation of Plan Recognition Systems p . 72 - 77 Procedural Agent Model for Plan
We propose a formal procedure-based agent model for plan recognition as an alternative to the declarative proposition-based agent model. Our formalism, called the Procedural Agent Model (PAM) allows us to describe procedural plans of agents in a concise and abstract way. Plan recognition uses PAM as a library of plan schemas and applies a graph-based pattern-matching algorithm to the observed e...
متن کاملMeeting plan recognition requirements for real-time air-mission simulations
In this paper, the potential synergy between instancebased pattern recognition and means-end (possible world) reasoning is explored, for supporting plan recognition in multi-aeroplane air-mission simulations. A combination of graph matching, induction, probabilistic principles and dynamic programming are applied to traces of aeroplane behaviour during flight manoeuvres. These satisfy the real-t...
متن کاملMulti-Agent Teamwork, Adaptive Learning, and Adversarial Planning in Robocup Using a PRS Architecture
Our approach for the Robocup97 competition is to emphasize teamwork among agents by augmenting reactions (based on awareness of the current situation) with predictions (based on predefined multiagent maneuvers). These predictions are accomplished by allowing agents to cooperatively accomplish predefined plans, which are elaborated reactively and hierarchically to ensure responsiveness to changi...
متن کاملUsing a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition
Plan recognition, the problem of inferring the goals or plans of an observed agent, is a key element of situation awareness in human-machine and machine-machine interactions for many applications. Some plan recognition algorithms require knowledge about the potential behaviours of the observed agent in the form of a plan library, together with a decision model about how the observed agent uses ...
متن کاملThe Automated Mapping of Plans for Plan Recognition
To coordinate with other agents in its an environment, an agent needs models of what the other agents are trying to do. When communication is impossible or expensive, this information must be acquired indirectly via plan recognition. Typical approaches to plan recognition start with specification of the possible plans the other agents may be following and develop special techniques for discrimi...
متن کامل