BDI Agent Construction Methodology
Make agents whose inner state, the beliefs, desires, and intentions, is written down and easy to inspect, so the behaviour can be explained and checked instead of just emerging.
Description
Build an agent from three parts that map to how people act on purpose. The beliefs are what the agent holds true. The desires are the goals it may take on. The intentions are the goals it has committed to and is acting on. A reasoning cycle drives it: each round it picks a plan from a plan library to meet a goal. This is the belief-desire-intention (BDI) approach from the Jason and JaCaMo line of tools. Beliefs are first-class data. Plans are first-class code. The cycle is out in the open. It shines when an LLM-only agent cannot show its goals or explain its reasoning, which BDI does by default.
When to apply
Reach for BDI when an agent must reason openly about goals, stick with long-running commitments, coordinate with other agents under shared rules, or stand up to an audit by a regulator. It fits multi-agent setups on tools such as Jason, JaCaMo, or Jadex. Don't apply it for one-shot generation, a light tool-using chatbot, or any task where no goal lives past a single turn. The BDI machinery is overhead for stateless work. Skip it too when the team has no appetite for symbolic agent programming.
What it involves
- Model the belief base
- Enumerate desires and adoption conditions
- Author the plan library
- Define selection functions
- Wire the deliberation cycle
- Integrate with environment and organisation
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