IRE Agent (Iterative Reflective Expansion)

The Iterative Reflective Expansion (IRE) Algorithm is a sophisticated reasoning framework that employs iterative hypothesis generation, simulation, and refinement to solve complex problems. It leverages a multi-step approach where an AI agent generates initial solution paths, evaluates their effectiveness through simulation, reflects on errors, and dynamically revises reasoning strategies.

Architecture

Workflow

Generate initial hypotheses
Simulate paths
Reflect on errors
Revise paths
Select promising paths
Synthesize solution

Class: `IterativeReflectiveExpansion`

Parameters

Parameter	Type	Default	Description
`agent_name`	`str`	`"General-Reasoning-Agent"`	Name of the internal reasoning agent
`description`	`str`	`"A reasoning agent that can answer questions and help with tasks."`	Description of the agent’s purpose
`agent`	`Agent`	`None`	Reserved for a Swarms agent instance; the constructor always builds and assigns its own internal `Agent` regardless of this value
`max_loops`	`int`	`5`	Maximum number of loops for the reasoning process
`system_prompt`	`str`	`GENERAL_REASONING_AGENT_SYS_PROMPT`	The system prompt for the internal agent
`model_name`	`str`	`"gpt-5.4"`	The underlying language model used by the internal agent
`output_type`	`OutputType`	`"dict"`	Format of the value returned by `run()`

Methods

Method	Description
`generate_initial_hypotheses`	Generates an initial set of reasoning hypotheses based on the problem input
`simulate_path`	Simulates a given reasoning path and evaluates its effectiveness
`meta_reflect`	Performs meta-cognitive reflection on the provided error information
`revise_path`	Revises the reasoning path based on the provided feedback
`select_promising_paths`	Selects the most promising reasoning paths from a list of candidates
`synthesize_solution`	Synthesizes a final solution from the promising paths and historical memory
`run`	Executes the Iterative Reflective Expansion process on the provided problem

Example

from swarms import IterativeReflectiveExpansion

agent = IterativeReflectiveExpansion(
    max_loops=3,
)

agent.run("What is the 40th prime number?")

Getting Started

Core Concepts

Agent Development

Reasoning Agents

Multi-Agent Architectures

Deployment & Operations

Integrations

CLI Reference

Changelog

IRE Agent (Iterative Reflective Expansion)

Architecture

Workflow

Class: `IterativeReflectiveExpansion`

Parameters

Methods

Example

​Architecture

​Workflow

​Class: IterativeReflectiveExpansion

​Parameters

​Methods

​Example

Architecture

Workflow

Class: `IterativeReflectiveExpansion`

Parameters

Methods

Example