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To increase prediction accuracy, novel learning algorithms are required in which agents collaborate to classify new examples while maintaining the privacy of ...
In many multiagent domains where classification tasks arise, agents have private features they are not willing to re- veal to other agents or humans. In this ...
We consider classification tasks where relevant features are distributed among a set of agents and cannot be centralized, for example due to privacy ...
Bibliographic details on Classification of Examples by Multiple Agents with Private Features.
May 1, 2024 · LangGraph is well-suited for creating multi-agent workflows because it allows two or more agents to be connected as a graph.
This study examines a mechanism design problem where the principal can affect the agents' knowledge of a payoff-relevant state.
Nov 19, 2023 · AI agents can be categorized into various types according to their attributes, including their reactivity or proactivity, the nature of their environment.
2 days ago · Explore different types of AI agents, their benefits, examples, use cases, and limitations in this guide. | ProjectPro.
In systems modeling, multi-agent approach is used to simulate the behavior of a complex model. For example, multi-agent approach has been successfully used to ...
Feb 26, 2024 · Agents can be categorized into five types: Simple Reflex agents, Model-based Reflex agents, Goal-based agents, Utility-based agents, and ...