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With the DLCS, we introduce mechanisms that satisfy both of these cases, while still providing compatible operation with the LCS. We introduce three types of messages that can be passed between DLCS agents. The first, the classifier message, allows agents to share learned information with one another, thereby helping agents benefit from each other's successes. The second, the action message, allows agents to \"talk\" to one another. The third, the bucket brigade algorithm payoff message, extends the chain rewarding payoff scheme of the standard LCS to multiple DLCS agents. Finally, we present some simulation results for both the standard LCS and the DLCS. Our LCS simulations examine some of the important aspects of learning classifier system operation, as well as illustrate some of the shortcomings. 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