"DAI [distributed artificial intelligence] is the study, construction, and application of multiagent systems, that is, systems in which several interacting, intelligent agents pursue some set of goals or perform some set of tasks."
Weiss (1999)
"An agent is a computational entity such as a software program or a robot that can be viewed as perceiving and acting upon its environment and that is autonomous in that its behavior at least partially depends on its own experience."
Weiss (1999)
"Surprisingly, there is no such agreement: there is no universally accepted definition of the term agent, and indeed there is a good deal of ongoing debate and controversy on this very subject. Essentially, while there is a general consensus that autonomy is central to the notion of agency, there is little agreement beyond this."
Weiss (1999)
"An agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives."
Weiss (1999)
"Multiagent systems are systems composed of multiple interacting computing elements, known as agents. Agents are computer systems with two important capabilities. First, they are at least to some extent capable of autonomous action – of deciding for themselves what they need to do in order to satisfy their design objectives. Second, they are capable of interacting with other agents – not simply by exchanging data, but by engaging in analogues of the kind of social activity that we all engage in every day of our lives: cooperation, coordination, negotiation, and the like."
Wooldridge (2002), page xi
"The idea of a multiagent system is very simple. An agent is a computer system that is capable of independent action on behalf of its user or owner. In other words, an agent can figure out for itself what it needs to do in order to satisfy its design objectives, rather than having to be told explicitly what to do at any given moment. A multiagent system is one that consists of a number of agents, which interact with one another, typically by exchanging messages through some computer network infrastructure."
Wooldridge (2002), page 3
"An agent is a computer system that is situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives."
Wooldridge (2002), page 15
A multiagent system is a system in which several interacting, autonomous, intelligent agents pursue some set of goals or perform some set of tasks.
Agent-based modelling can stand accused of being poor science. To do science, we needs ways to test hypotheses and reach general conclusions.
Too many free parameters. One can vary any free parameters until one obtains the result that one desires, e.g. fat tails in finance.
Too many possible explanations of the results (the opportunity for story telling).
No general theoretical way to know whether a given simulation configuration is the only way to get from some set of initial conditions to a result or one of a family of hundreds or millions of ways to get to a result.
Model validation can be complicated.
Difficult to verify that the models are consistent enough to be useful.
Railsback (2001) addresses the problem of getting ‘results’—general principles and conclusions—from multiagent systems and recommends a pattern-oriented approach.