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Behavior-Based Robotics

Reactive vs. Deliberative Strategies

There is still considerable debate over the optimal role of internal representation. (Clark & Grush 1999) Many researchers believe that a robot cannot assign meaning to its actions or environment without representing them, even if indirectly. (Pylyshyn 1987) (Fodor 1987) Others believe that reliance on internal representation thwarts a robot’s ability to act quickly across domains. An important figure for the field of behavior-based robotics, Rodney Brooks, declared planning to be “just a way of avoiding figuring out what to do next.” (Brooks 1987)

Strategies which require that action be mediated by some symbolic representation of the environment are often called deliberative. In contrast, reactive strategies do not exhibit a steadfast reliance on internal models, but displace some of the role of representation onto the environment itself. Instead of responding to entities within a model, the robot can respond directly to perception of the real world. Thus, reactive systems are best characterized by a direct connection between sensors and effectors. Control is not mediated by a model but rather occurs as a low level pairing between stimulus and response.

If a task is highly structured and predictable it may make sense to use a deliberative approach. For example, if an intelligent agent is embedded in an entirely virtual environment, then it is often possible to encode every aspect of the environment with some semantic representation. In complex, real-world domains where uncertainty cannot be effectively modeled, however, robots must have a means of reacting to an infinite number of possibilities.

Some behavior-based strategies use no explicit model of the environment. In the late 1980’s Schoppers believed that if a programmer knew enough about an environment, s/he could make a set of stimulus-response pairs sufficient to cover every possibility. (Schoppers 1989) Clearly, such an approach is only possible in restricted domains such as a chess game or micro-world where there are a limited number of possible states. For more complicated domains it is necessary to find an appropriate balance between reactive and deliberative control.

Systems that seek to completely avoid internal representation are ill-equipped for the many tasks that require memory or communication. On the other hand, systems that must transmute all perception and action through an internal model will be necessarily confounded in some new environment. The key is that the model should not drive development. Rather, control should be built from the bottom up and distributed across the system. For a reactive design methodology to work, it is necessary that behavior be decomposed into atomistic components. Often, design will include a developmental phase during which these components can be honed and joined together. First, the designer builds a minimal system and then exercises it, using an ongoing loop to evaluate performance and add new competence.


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