Unified Cognitive Assistant Agents for IoT Coordination
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Solution Overview
Problem
Conventional embodied cognition systems focus on a single object interacting with multiple users, lacking the ability to manage and coordinate multiple cognitive assistant agents across different domains, leading to fragmented and inefficient cognitive assistance experiences.
Innovation Solution
A computer-implemented method and system that couples Internet of Things (IoT) devices to a cognitive model with a cognitive classifier, enabling unified cognition by identifying rules and events across multiple domains, allowing for dynamic loading and coordination of cognitive assistant agents to provide integrated and inter-operable cognitive assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional embodied cognition systems focus on a single object with preloaded functions, then the system structure is simple and easy to implement, but the system lacks the ability to manage and coordinate multiple cognitive assistant agents across different domains
Solution Approach 1:
The patent segments the cognitive assistance system into multiple independent cognitive assistant agents, each responsible for specific domains or functions. These agents can be dynamically loaded and coordinated by a central management system, allowing the system to handle multiple domains while maintaining manageable complexity through modular organization.
Solution Approach 2:
The patent creates a universal cognitive assistant agent framework that can perform multiple functions across different domains. The cognitive assistant agent is designed with multi-functionality, capable of interacting with various IoT devices and handling different types of cognitive tasks through a unified interface and common reasoning capabilities.
2Adaptability or versatility
If multiple cognitive assistant agents are introduced to cover different domains, then the system becomes more versatile and adaptive, but the system complexity increases and coordination becomes difficult
Solution Approach 1:
The patent introduces a central cognitive model as an intermediary that coordinates between multiple cognitive assistant agents and IoT devices. This mediator manages the interactions, resolves conflicts, and ensures coherent operation across different domains, reducing the coordination complexity that would otherwise arise from direct peer-to-peer interactions between multiple agents.
Solution Approach 2:
The patent adds a new organizational dimension by introducing hierarchical structure with cognitive models at one level and cognitive assistant agents at another. This dimensional change in system organization allows multiple agents to operate independently at their level while being coordinated through the hierarchical structure, managing complexity through layered architecture.
3Ease of operation
If a single embodied cognition object interacts generically with multiple users, then the implementation is straightforward, but the system cannot provide personalized and integrated cognitive assistance across different contexts
Solution Approach 1:
The patent performs preliminary actions by pre-configuring cognitive assistant agents with domain-specific knowledge and capabilities before they interact with users. The system pre-loads appropriate agents based on predicted user needs and contexts, enabling personalized assistance without requiring complex real-time adaptation during interactions.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting which cognitive assistant agents are active based on user context, device state, and interaction history. The system changes operational parameters such as agent selection, activation levels, and interaction modes to provide personalized assistance while maintaining implementation simplicity through rule-based parameter adjustment.
Data Source
AI summary
Provided are techniques for unified cognition for a virtual personal cognitive assistant. Internet of Things (IoT) devices are coupled to a cognitive model, wherein the cognitive model includes a cognitive classifier, and wherein the cognitive classifier includes a cognitive dimension map and a recognition process. Input from one or more of the IoT devices is received. The cognitive dimension map is used to identify rules based on the input. The recognition process is used to identify events based on the rules. Then, the events are issued to one or more of the IoT devices, wherein the one or more IoT devices execute actions in response to the events.