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(Related publications: [PUBLink] [PUBLink])

Triggering agents introduce internal states. Past information can thus be utilized by the rules, and sequences of actions can be executed to attain longer-term goals. A possible rule might look like this:

IF (distribution_mode) AND (leading_helicopter == left) THEN
  turn_right
  trigger_acceleration_mode
ENDIF

Popular Alife agent systems like CyberLife's Creatures [PUBLink], P.F. Magic's Virtual Petz [PUBLink] and Brooks' subsumption architecture [PUBLink] are examples of this category. Indeed, nearly all of today's computer games apply this approach, using finite state machines to implement it.

These agents can react as fast as reactive agents and also have the ability to attain longer-term goals. But they are still based on hard-wired rules and cannot react appropriately to situations that were not foreseen by the programmers or have not been previously learned by the agents (e.g., by neural networks).

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Last update:
May 19, 2001 by Alexander Nareyek