Artificial Social Mind for Multi-Agent Coordination
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Solution Overview
Problem
Managing interdependence between dispersed agents in complex and dynamic environments is challenging due to the need for encoding inter-agent rules, handling differing and incomplete views, and unanticipated events, making it computationally intractable to predict and preprogram all necessary interactions without a central processor.
Innovation Solution
The implementation of an Artificial Social Mind (ASM) component that enables agents to form and navigate social relationships, attribute mental states, and understand differing desires and intentions within an Artificial Social Network, allowing for autonomous interaction and decision-making without a central manager.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a central processor is used to manage interactions between agents, then coordination and control are simplified, but system complexity and cost increase
Solution Approach 1:
The patent extracts the social intelligence functionality from a central processor and embeds it within individual agents through Artificial Social Mind (ASM) components. Each agent now independently possesses the capability to understand social contexts, attribute mental states to others, and make autonomous decisions about interactions, eliminating the need for centralized coordination while maintaining effective multi-agent cooperation.
2Reliability
If inter-agent rules are preprogrammed to handle all scenarios, then agent interactions become predictable and controlled, but the system becomes computationally intractable in complex dynamic environments
Solution Approach 1:
The patent implements dynamic mental state attribution where agents continuously update their understanding of other agents' beliefs, desires, and intentions based on observed actions and contextual information. This dynamic approach allows agents to adapt to changing environments and unanticipated events without requiring exhaustive preprogramming of all possible scenarios, making the system computationally feasible while maintaining reliable interactions.
Solution Approach 2:
Each agent equipped with an ASM component independently performs mental state attribution and decision-making for its interactions with other agents. This self-service capability allows agents to autonomously navigate complex social situations without requiring external computation or centralized rule enforcement, significantly reducing the computational burden on the overall system.
3Adaptability or versatility
If agents operate autonomously without central management, then system flexibility and adaptability increase, but coordination and social behavior management become challenging
Solution Approach 1:
The Artificial Social Mind (ASM) component serves as an intermediary within each agent that handles social behavior management. The ASM enables agents to attribute mental states to other agents, understand social contexts, and make autonomous decisions about interactions. This intermediary functionality provides the structure needed for coordinated behavior while preserving agent autonomy and flexibility in dynamic environments.
Data Source
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AI summary
A method for creating a subnetwork within a computerized network is provided. The method includes forming a computerized component representative of an agent linked to the network, the computerized component including first data relating to an environment state of the agent, second data relating to at least one desire of the agent, and third data relating to at least one capability of the agent; and providing the computerized component with an ability to link to other computerized components to form subnetworks with the at least one computerized component in accordance with the first second and third data.