Our work presents agent-based market model for a financial market based on the Minority Game (MG). Grand-canonical MG itself shows many interesting features such as coordination of agents, collective behavior, adaptation of agents, insignificance of real memory known to agents for achieving coordination and many others. These features proven to be very useful for computational models for complex adaptive systems such as financial markets and information network. The only information available to agents in MG is historical minority choices. Our work presents extension of MG in which agents have access for additional information about their environment; they know about next turn choices of their neighbors and try to utilize this information for better predictions for future price changes. In this way agent even has a possibility to adapt strategies of successful neighbor or to learn to avoid bad advices. It could be useful to understand how this form of communication affects the emergent features of the model, particularly agents' ability to coordinate.

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