ai-mirow-projects
/
swarms
mirror of https://github.com/kyegomez/swarms
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

fix reasoning agent docs

Browse Source
pull/970/merge
Kye Gomez 4 days ago
parent 15a2622d63
commit 234138c75d
1 changed files with 37 additions and 0 deletions
Show Stats Download Patch File Download Diff File

37
docs/swarms/agents/reasoning_agents_overview.md
Unescape View File

@ -19,6 +19,7 @@ These agents are inspired by cognitive science and human reasoning processes, in
## Available Reasoning Agents ## Available Reasoning Agents
| Agent Name | Type | Research Paper | Key Features | Best Use Cases | Implementation | Documentation | | Agent Name | Type | Research Paper | Key Features | Best Use Cases | Implementation | Documentation |
@ -38,11 +39,16 @@ These agents are inspired by cognitive science and human reasoning processes, in
**Description**: Implements multiple independent reasoning paths with consensus-building to improve response reliability and accuracy through majority voting mechanisms. **Description**: Implements multiple independent reasoning paths with consensus-building to improve response reliability and accuracy through majority voting mechanisms.
**Key Features**: **Key Features**:
- Concurrent execution of multiple reasoning instances - Concurrent execution of multiple reasoning instances
- AI-powered aggregation and consensus analysis - AI-powered aggregation and consensus analysis
- Validation mode for answer verification - Validation mode for answer verification
- Configurable sample sizes and output formats - Configurable sample sizes and output formats
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -78,11 +84,16 @@ graph TD
**Description**: Dual-agent collaborative system that separates reasoning and execution phases, enabling specialized analysis and task completion through coordinated agent interaction. **Description**: Dual-agent collaborative system that separates reasoning and execution phases, enabling specialized analysis and task completion through coordinated agent interaction.
**Key Features**: **Key Features**:
- Separate reasoning and execution agents - Separate reasoning and execution agents
- Collaborative problem decomposition - Collaborative problem decomposition
- Cross-validation between agents - Cross-validation between agents
- Configurable model selection for each agent - Configurable model selection for each agent
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -115,11 +126,16 @@ graph TD
**Description**: Sophisticated reasoning framework employing iterative hypothesis generation, simulation, and refinement through continuous cycles of testing and meta-cognitive reflection. **Description**: Sophisticated reasoning framework employing iterative hypothesis generation, simulation, and refinement through continuous cycles of testing and meta-cognitive reflection.
**Key Features**: **Key Features**:
- Hypothesis generation and testing - Hypothesis generation and testing
- Path simulation and evaluation - Path simulation and evaluation
- Meta-cognitive reflection capabilities - Meta-cognitive reflection capabilities
- Dynamic strategy revision based on feedback - Dynamic strategy revision based on feedback
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -153,11 +169,16 @@ graph TD
**Description**: Advanced self-reflective system implementing actor-evaluator-reflector architecture for continuous improvement through experience-based learning and memory integration. **Description**: Advanced self-reflective system implementing actor-evaluator-reflector architecture for continuous improvement through experience-based learning and memory integration.
**Key Features**: **Key Features**:
- Actor-evaluator-reflector sub-agent architecture - Actor-evaluator-reflector sub-agent architecture
- Self-evaluation and quality assessment - Self-evaluation and quality assessment
- Experience memory and learning capabilities - Experience memory and learning capabilities
- Adaptive improvement through reflection - Adaptive improvement through reflection
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -195,11 +216,16 @@ graph TD
**Description**: Knowledge-driven reasoning system that generates relevant information before answering queries, implementing multi-perspective analysis through coordinated knowledge synthesis. **Description**: Knowledge-driven reasoning system that generates relevant information before answering queries, implementing multi-perspective analysis through coordinated knowledge synthesis.
**Key Features**: **Key Features**:
- Dynamic knowledge generation - Dynamic knowledge generation
- Multi-perspective reasoning coordination - Multi-perspective reasoning coordination
- Information synthesis and integration - Information synthesis and integration
- Configurable knowledge item generation - Configurable knowledge item generation
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -237,11 +263,16 @@ graph TD
**Description**: Specialized evaluation system for assessing agent outputs and system performance, providing structured feedback and quality metrics through comprehensive assessment frameworks. **Description**: Specialized evaluation system for assessing agent outputs and system performance, providing structured feedback and quality metrics through comprehensive assessment frameworks.
**Key Features**: **Key Features**:
- Structured evaluation methodology - Structured evaluation methodology
- Quality assessment and scoring - Quality assessment and scoring
- Performance metrics generation - Performance metrics generation
- Configurable evaluation criteria - Configurable evaluation criteria
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -273,11 +304,16 @@ graph TD
**Description**: Action-oriented reasoning system implementing iterative reason-act-observe cycles with memory integration for interactive task completion and environmental adaptation. **Description**: Action-oriented reasoning system implementing iterative reason-act-observe cycles with memory integration for interactive task completion and environmental adaptation.
**Key Features**: **Key Features**:
- Reason-Act-Observe cycle implementation - Reason-Act-Observe cycle implementation
- Memory integration and experience building - Memory integration and experience building
- Action planning and execution - Action planning and execution
- Environmental state observation - Environmental state observation
**Architecture Diagram**: **Architecture Diagram**:
```mermaid ```mermaid
@ -384,6 +420,7 @@ For comprehensive technical documentation on each reasoning agent implementation
- [Reasoning Agent Router](reasoning_agent_router.md) - [Reasoning Agent Router](reasoning_agent_router.md)
--- ---
Reasoning agents represent a significant advancement in enterprise agent capabilities, implementing sophisticated cognitive architectures that deliver enhanced reliability, consistency, and performance compared to traditional language model implementations. Reasoning agents represent a significant advancement in enterprise agent capabilities, implementing sophisticated cognitive architectures that deliver enhanced reliability, consistency, and performance compared to traditional language model implementations.
Write Preview
Loading…
Cancel
Save