Published Article / To enable meaningful and consistent communication between different software systems in a particular domain (such as manufacturing, law or medicine), a standardised vocabulary and communication language is required by all the systems involved. Concepts in the domain about which the systems want to communicate are formalized in an ontology by establishing the meaning of concepts and creating relationships between them. The inputs to this process in found by analysing the physical domain and its processes. The resulting ontology structure is a computer useable representation of the physical domain about which the systems want to communicate. To enable the long term persistence of the actual data contained in these concepts and the enforcement of various business rules, a sufficiently powerful database system is required. This paper presents the design of a manufacturing ontology and its accompanying relational database schema that will be used in a manufacturing test domain.

Presently, most spacecraft are controlled from ground involving activities such as up-linking the schedule of daily operations and monitoring health parameters. These activities lead to a cognitive overload on human operators. Imaging/science opportunities are lost, if any discrepancies occur during the execution of pre-planned sequences. Consequently, advanced space exploration systems for future needs demand on-board intelligence and autonomy. This thesis attempts to solve the problem of providing an adequate degree of autonomy in future generation of spacecraft. The autonomous spacecraft accept high-level goals from users and make decisions on-board to generate detailed command schedules satisfying stringent constraints posed by the harsh environment of the space, visibility criteria and scarce on-board resources. They reconfigure themselves in case of any failure and re-plan when needed. Autonomy concepts are derived in the context of complex systems by drawing analogy to living organisms and social organisations. A general autonomy framework may be defined with a six level structure comprising of the following capabilities -reflexes, awareness, self-regulation, self-healing, self-adaptation and self-evolution. A generic and reusable software architecture is proposed using hybrid multi-agent systems, which are arranged in a hierarchical manner using two types of decomposition viz. stratum and layer. The software architecture of the autonomous spacecraft is modeled as a stratified agent with a deliberative stratum, which achieves adaptive behaviour and a reactive stratum, which achieves reactive behaviour. Each individual agent has a generic structure comprising of perception, action, communication and knowledge components. It achieves the specialist capability through model-based reasoning. The knowledge models encompass: Planning knowledge describing higher-level goals, task structure and method of achieving the goals, Control knowledge encompassing the static and dynamic models of the spacecraft and Diagnostic knowledge incorporating the cause-effect relationships. The deliberative stratum is capable of planning in different time horizons and is, in turn, organised into a hierarchical agent system with three layers corresponding to different time horizons. It is composed of a long-term, medium-term and short-term planning agents, focusing on strategic issues, spacecraft level resources and specific spacecraft states respectively. The power of Petri nets is exploited for knowledge modeling as well as for plan representation. The ability of Petri nets to represent causality, concurrency and conflict relations explicitly makes it an excellent tool for representing the planning problem. Hierarchical Timed Petri Net is chosen for our modeling, since it captures the temporal requirements of the real-time spacecraft operations as well as facilitates the modeling of the system with multiple levels of abstraction. The necessary primitives for the plan representation are defined. In hierarchical modeling using Petri nets, refinement is done by a compound (high-level) transition. A compound transition models either a complex activity, which corresponds to high-level operation on spacecraft or a method, which corresponds to the agent capability. At the lowest layer, a transition in the plan represents a primitive command to the spacecraft, such as ‘switch on camera’. The Petri net unfolding technique, which is a partial order approach, is applied to derive the plans from the dynamic knowledge models. This tackles the problem of combinatorial explosion. A hierarchical planning approach is followed, in which the abstract plan is recursively decomposed using the unfolding technique and refined by way of exercising the appropriate decisions in each layer. The reactive stratum is configured with three peer level agents. The control agent executes the command schedule and has the capability for reflex action. Structural properties of Petri nets are exploited by the execution-monitoring agent and the diagnostic agent for system level diagnosis. Fault tree method is applied for fine granularity diagnosis. The resultant architecture is a cost-effective solution, since it permits reusability of knowledge models across similar missions. The knowledge models are formally verified for ensuring the absence of deadlocks, buffer overflows, recoverability and detection of unreachable modules using Petri net properties such as reachability, liveness, boundedness, safeness, reversibility and home state. The high-risk components are subjected to safety property verification, which makes the system rugged. The hierarchical composition of Petri net models (which are independently verified), preserves liveness and boundedness characteristics and thus ensuring the reliability of the integrated models. This, in turn, ensures that reliable plans are generated on-board using these good quality models. The models of the system components viz. partial order plan, conditional plan, dynamic world model, reflex model, resource model and the hierarchical models are developed and demonstrated using HPSIM and Moses Tool Suite, using examples from spacecraft domain. The long-term planning agent, with hierarchical world models, for handling high-level goals is developed and simulated using Moses Tool Suite. The plan generation using unfolding approach is demonstrated using VIPTool, which has the partial order analysis capability. In summary, the main contributions include (a) Definition of a general framework for spacecraft autonomy; (b) design of a generic and reusable architecture for autonomous spacecraft using hybrid multi-agent concepts; (c) unified knowledge representation and reasoning using Petri nets across various strata/layers; (d) application of Petri net unfolding technique in a hierarchical manner for plan generation; (e) use of structural properties of Petri nets for fault identification and location; (f) verification and validation of Petri net models using Petri net properties and (g) simulation and demonstration of the system components viz. partial order plan, conditional plan, dynamic world model, reflex model, resource model and hierarchical models, by developing examples from spacecraft domain, using HPSIM and Moses Tool Suite and demonstration of plan generation using unfolding technique using VIPTool.

Simulation has been used to model combat for a long time. Recently, it has been accepted that combat is a complex adaptive system (CAS). Multi-agent systems (MAS) are also considered as a powerful modelling and development environment to simulate combat. Agent-based distillations (ABD) - proposed by the US Marine Corp - are a type of MAS used mainly by the military for exploring large scenario spaces. ABDs that facilitated the analysis and understanding of combat include: ISAAC, EINSTein, MANA, CROCADILE and BactoWars. With new concepts such as networked forces, previous ABDs can implicitly simulate a networked force. However, the architectures of these systems limit the potential advantages gained from the use of networks. In this thesis, a novel network centric multi-agent architecture (NCMAA) is pro-posed, based purely on network theory and CAS. In NCMAA, each relationship and interaction is modelled as a network, with the entities or agents as the nodes. NCMAA offers the following advantages: 1. An explicit model of interactions/relationships: it facilitates the analysis of the role of interactions/relationships in simulations; 2. A mechanism to capture the interaction or influence between networks; 3. A formal real-time reasoning framework at the network level in ABDs: it interprets the emergent behaviours online. For a long time, it has been believed that it is hard in CAS to reason about emerging phenomena. In this thesis, I show that despite being almost impossible to reason about the behaviour of the system by looking at the components alone because of high nonlinearity, it is possible to reason about emerging phenomena by looking at the network level. This is undertaken through analysing network dynamics, where I provide an English-like reasoning log to explain the simulation. Two implementations of a new land-combat system called the Warfare Intelligent System for Dynamic Optimization of Missions (WISDOM) are presented. WISDOM-I is built based on the same principles as those in existing ABDs while WISDOM-II is built based on NCMAA. The unique features of WISDOM-II include: 1. A real-time network analysis toolbox: it captures patterns while interaction is evolving during the simulation; 2. Flexible C3 (command, control and communication) models; I 3. Integration of tactics with strategies: the tactical decisions are guided by the strategic planning; 4. A model of recovery: it allows users to study the role of recovery capability and resources; 5. Real-time visualization of all possible information: it allows users to intervene during the simulation to steer it differently in human-in-the-loop simulations. A comparison between the fitness landscapes of WISDOM-I and II reveals similarities and differences, which emphasise the importance and role of the networked architecture and the addition of strategic planning. Lastly but not least, WISDOM-II is used in an experiment with two setups, with and without strategic planning in different urban terrains. When the strategic planning was removed, conclusions were similar to traditional ABDs but were very different when the system ran with strategic planning. As such, I show that results obtained from traditional ABDs - where rational group planning is not considered - can be misleading. Finally, the thesis tests and demonstrates the role of communication in urban ter-rains. As future warfighting concepts tend to focus on asymmetric warfare in urban environments, it was vital to test the role of networked forces in these environments. I demonstrate that there is a phase transition in a number of situations where highly dense urban terrains may lead to similar outcomes as open terrains, while medium to light dense urban terrains have different dynamics