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agent-opt

Open Source
Optimization Frameworks Updated Feb 24, 2026
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Overview

Agent-opt is an open-source optimization engine designed to improve the performance of autonomous agents. It provides a framework for optimizing agent behavior and decision-making. The engine is developed and maintained by the future-agi community on GitHub.

Problem It Solves

Suboptimal agent performance

Target Audience: Artificial Intelligence Researchers and Developers

Inputs

  • • Agent models
  • • Environment data
  • • Optimization objectives

Outputs

  • • Optimized agent policies
  • • Performance metrics
  • • Agent behavior analysis

Example Workflow

  1. 1 Agent model definition
  2. 2 Environment simulation
  3. 3 Optimization objective specification
  4. 4 Optimization algorithm selection
  5. 5 Training and evaluation
  6. 6 Policy refinement

Sample System Prompt 


              Optimize the policy of a reinforcement learning agent to maximize cumulative reward in a complex environment.

Tools & Technologies

PyTorch TensorFlow Gym

Alternatives

  • • Ray Tune
  • • Optuna
  • • Hyperopt

FAQs

Is this agent open-source?
Yes
Can this agent be self-hosted?
Yes
What skill level is required?
Advanced