Semantic Approach to Dynamic Coordination in Autonomous Systems Artem Katasonov and Vagan Terziyan University of Jyväskylä, Finland artem.katasonov@jyu.fi, vagan@jyu.fi Abstract In open systems where the components, i.e. the agents and the resources, may be unknown at design time, or in dy- namic and self-organizing systems evolving with time, there is a need to enable the agents to communicate their inten- tions with respect to future activities and resource utiliza- tion to resolve coordination issues dynamically. Ideally, we would like to allow ad-hoc interaction, where two stand- alone independently-designed systems are able to coordi- nate whenever a need arises. The Semantic Web based ap- proach presented in this paper aims at enabling agents to coordinate without assuming any design-time ontological alignment of them. An agent can express an action inten- tion using own vocabulary, and through the process of dy- namic ontology linking other agents will be able to arrive at a practical interpretation of that intention. We also show how our approach can be realized on top of the Semantic Agent Programming Language. 1 Introduction Coordination is one of the fundamental problems in sys- tems composed of multiple interacting processes [17]. Co- ordination aims at avoiding negative interactions, e.g. when two processes conflict over the use of a non-shareable re- source, as well as exploiting positive interactions, e.g. when an intermediate or final product of one process can be shared with another process to avoid unnecessary repetition of actions. A classic example of a negative interaction from the field of agent-based systems is two robots trying to pass thorough a door at the same time and blocking each other. A corresponding example of a positive interaction is a robot opening and closing the door when passing it while also letting the other robot to pass, in so saving it the need of opening/closing the door by itself. The pre-dominant approach has been to hard-wire the co- ordination mechanism into the system structure [17]. Syn- chronization tools such as semaphores have been tradition- ally used to handle negative interactions, requiring every process to be programmed to check the semaphore before accessing the resource (like checking if there is an ”occu- pied” light over a lavatory door). If a resource is occupied by a process for a significant time, it would be clearly bet- ter for the other process to work on another its task rather than just wait. Under the traditional approach, realizing that as well as attempting to exploit any positive interactions is possible only through additional hard-wiring: the programs of the processes must have incorporated some knowledge about the behavior of each other. This traditional approach becomes insufficient when considering more open systems, where the processes and resources composing the system may be unknown at design time [4]. In such systems, we ideally want computational processes to be able to reason about the coordination issues in their system, and resolve these issues autonomously [4]. One way to achieve this is to enable the relevant processes to communicate their intentions with respect to future ac- tivities and resource utilization [12]. Jennings [7] presents this as an issue of enabling individual agents to represent and reason about the actions, plans, and knowledge of other agents to coordinate with them. Tamma at al. [17, 12] developed an ontological frame- work for dynamic coordination. They stated the need for an agreed common vocabulary, with a precise semantics, that is therefore suitable for representation as an ontology. [17] provided such an ontology that defined coordination in terms of agents carrying out activities involving some re- sources, which can be non-shareable, consumable, etc. [12] described then the rules for checking for conflicts among ac- tivities: e.g. if two activities overlap in time and require the same non-shareable resource, they are mutually-exclusive. [12] also described some possible coordination rules to be followed when a conflict of a certain type is detected. The ontology of Tamma et al. is an upper ontology, i.e. an ontology which attempts to describe the concepts that are the same across all the domains of interest. Roughly speaking, the idea is to make the agents to communicate their intentions and actions using the upper-ontology con- cepts (i.e. ”resource”, ”activity”) rather than the domain- ontology concepts (e.g. ”printer”, ”printing document”) and