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In this article we focus on the essential requirements of a robot for semantically dealing with cooperative problem solving in a natural setting such as discovery of exit from a labyrinth. A very common application area for such robots are used as set of multi-agents at junctions in Traffic Management and Information Systems (TMIS) to manage the traffic and interact with ambulance or fire fighters to traverse the shortest possible path . In order to present the above mentioned goal, a new modular architecture for design and implementation of cooperative labyrinth discovery robots (CLDRs) is presented. The labyrinth data structure (Maze Set) is represented in notation 3 format useful for semantic logic data processing purposes. This facilitates semantic web services on each CLDR (agent). Each agent is an autonomous system which acts based on its sensors and information retrieved from other agents. Our aim is creating robotic agents based on semantic web services and implementing autonomous semantic agents (ASAs). Numerous domains are likely application areas for multiple ASAs (MASAs), such as systems for distributed control, decision support, and financial market projection. Initial application area will be "Cooperative Labyrinth Discovery" where MASA robots cooperatively inspect an uncharted maze to discover its exits. Hence, context awareness, semantic understanding, near area communication, and friend/foe distinction make up upper value sets loaded upon "automaton" nature of a robotic ASA. We are aiming at effecting coordination and cooperation among MASAs towards succeeding a shared goal through semantic web theory and techniques.