best reply definition
best reply strategy means that a replanning agent can construct the optimal response to a given situation of the environment. An example is the selection of a shortest path in a time-dependent network. In complex systems, the assumption that agents perform such strategy selection seems unreasonable because it contradicts the cognitive ability of humans: travelers cannot discriminate, following the same example, two paths that differ by one second. Nevertheless, best reply strategies are appealing because we can borrow much from Operation Research and Computer Science to implement the decision model. The approach of random utility theory relaxes these assumptions by assigning higher probabilities to strategies with higher outcomes. By doing so, similar alternatives will be selected with similar probabilities. This theory has two main drawbacks: firstly, there is always a finite (though small) probability that agents are going to select a very low utility option; secondly, it is based on the assumption that users face or are aware of all the potential outcomes, which is also not realistic from the behavioral point of view. An alternative to these approaches is to borrow a method from Complex Adaptive Systems, where possible solutions are permanently added and removed. The system then choses between those solutions with probabilities that may resemble random utility theory. An implementation of this may look as follows (Raney and Nagel, 2002, 2003):
best reply strategy means that a replanning agent can construct the optimal response to a given sit- uation of the environment. An example is the selection of a shortest path in a time-dependent network. In complex systems, the assumption that agents perform such strategy selection seems unreasonable be- cause it contradicts the cognitive ability of humans: travelers cannot discriminate, following the same example, two paths that differ by one second. Nevertheless, best reply strategies are appealing because we can borrow much from Operations Research and Computer Science to implement the decision model. The approach of random utility theory relaxes these assumptions by assigning higher probabilities to