Location-Based Reasoning about Complex Multi-Agent Behavior
نویسندگان
چکیده
منابع مشابه
Location-Based Reasoning about Complex Multi-Agent Behavior
Recent research has shown that surprisingly rich models of human activity can be learned from GPS (positional) data. However, most effort to date has concentrated on modeling single individuals or statistical properties of groups of people. Moreover, prior work focused solely on modeling actual successful executions (and not failed or attempted executions) of the activities of interest. We, in ...
متن کاملReasoning about Autonomy in Multi-Agent Systems
A domain-independent approach to reasoning about the autonomy level of agent goals is presented. The approach is based on general representations of knowledge about goals and resources. A hybrid two-stage reasoning process is proposed, consisting of a belief net and a case-based reasoner. Belief nets are examined in detail as a mechanism for establishing the basic autonomy level of an agent for a
متن کاملReasoning about strategies of multi-agent programs
Verification of multi-agent programs is a key problem in agent research and development. This paper focuses on multi-agent programs that consist of a finite set of BDI-based agent programs executed concurrently. We choose alternating-time temporal logic (ATL) for expressing properties of such programs. However, the original ATL is based on a synchronous model of multi-agent computation while mo...
متن کاملImproving Agent Performance for Multi-Resource Negotiation Using Learning Automata and Case-Based Reasoning
In electronic commerce markets, agents often should acquire multiple resources to fulfil a high-level task. In order to attain such resources they need to compete with each other. In multi-agent environments, in which competition is involved, negotiation would be an interaction between agents in order to reach an agreement on resource allocation and to be coordinated with each other. In recent ...
متن کاملMulti-Agent, Multi-Case-Based Reasoning
A new paradigm for case-based reasoning described here assembles a set of cases similar to a new case, solicits the opinions of multiple agents on them, and then combines their output to predict for a new case. We describe the general approach, along with lessons learned and issues identified. One application of the paradigm schedules constraint satisfaction solvers for parallel processing, bas...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2012
ISSN: 1076-9757
DOI: 10.1613/jair.3421