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necessarily have correct solutions. Collaboration further complicates this issue
because it involves coordinating with other agents in a creative process. For these
reasons, collaborative creativity is an extremely diffi cult target for traditional AI
approaches.
This crack in the theoretical foundation of AI and computational creativity once
seemed like a problem that would only take more computing power, larger knowl-
edge bases, and more sophisticated machine-learning algorithms to solve. However,
we think this problem refl ects a larger systemic issue stemming from the basic
assumptions about the nature of human cognition in AI and computational creativ-
ity. Once cognition and creativity are reframed in an enactive perspective, these hard
problems become much more manageable.
Computationally creative systems employing the enactive perspective are based
on a continually fl owing and dynamic interaction with an environment rather than
discrete actions and goal-oriented planning. An enactive investigation of creativity
therefore begins at the level of perception, action, an environment, and the feedback
loop that emerges during interaction. Enactive agents learn by experimentally inter-
acting with their environment and perceiving the effects of those actions in a feed-
back loop, similar to a baby fi rst learning to make sense of her senses. From this
perspective, learning takes place when actions that produce a pleasing perceptual
correlate (including a reaction from another agent, such as a mother cooing) are
remembered as a percept-action pairing. These percept-action pairings are then
repeated and built upon in an attempt to create shared meaning and experiences
through participatory sensemaking, whereby agents coordinate their intentions
through interaction and negotiation (Stewart et al.
2010
).
The enaction theory describes creativity as a continual process whereby cogni-
tive agents adaptively and experimentally interact with their environment through a
continuous perception-action feedback loop to produce structured, organized, and
meaningful interactions in an emergent process of sensemaking (or participatory
sensemaking when multiple agents are collaborating). The emergent sensemaking
process that results in creativity is fundamentally based on (and therefore inextrica-
bly bound to) continuous real-time interaction between an agent and its environ-
ment. During this type of emergent creativity, loose “directives” that guide actions
are negotiated and fl uidly defi ned, refi ned, or discarded altogether depending on
how other collaborating agents and the environment respond to the agent's actions.
While an enactive agent still defi nes directives that serve to guide actions, these
directives merely constrain (rather than constitute) possible opportunities to explore
in the environment.
In this process, experience, practice, and concentration help develop more
nuanced and detailed percept-action couplings that afford a greater depth of interac-
tion with the world. This means we cannot explain expertise relying exclusively on
huge databases of representations manipulated in a rule-based manner (like case-
based reasoning, analogical reasoning, blending, evolutionary algorithms, etc.).
Experts know exactly where to look, what to look at, and when to look at it to fi gure
out how to effectively navigate their domain of expertise. If the right information is
not available, then experts know how to either restructure their sensory information
