The need for responsive, flexible agents is pervasive in many application domains due to their complex, dynamic, and uncertain nature. Dynamic Adaptive Autonomy allows Sensible Agents to reorganize themselves during system operation to solve different problems in the face of these complex and dynamic environments. This paper presents both functional and implementation architectures for Sensible Agent systems. The functional architecture supports concepts from the distributed computing community by separating internal agent functionality into a discrete set of modules whose interactions are formally specified using the Interface Definition Language (IDL) from the Common Object Request Broker Architecture (CORBA). These four modules are: (1) Perspective Modeler--which contains the agent's explicit model of its local, subjective view of the world, (2) Autonomy Reasoner--determines the appropriate decision-making framework for each of the agent's goals, (3) Action Planner--interprets domain-specific goals, plans to achieve these goals and executes the generated plans, and (4) Conflict Resolution Advisor--identifies, classifies, and recommends possible solution strategies for resolving conflicts between this agent and other agents. The implementation architecture has been realized in a testbed that promotes (1) language and platform independence, (2) parallel development, (3) rapid integration of evolving representations and algorithms implementing agent functionality, (4) repeatable experimentation and testing, (5) environment and agent visualization, and (6) inter-domain application portability. The testbed uses the Inter-Language Unification (ILU) ORB from Xerox to provide the CORBA layer of inter-module and inter-agent communication. A three-dimensional visualization of the domain is provided with a CORBA-connected Virtual Reality Modeling Language (VRML) model while low-level data collection is accomplished using a CORBA-connected Java application. The combination of a distributed functional architecture with a distributed implementation architecture provides a high level of flexibility, visualization ability and experimental fidelity for evaluating the performance of Sensible Agents in complex, dynamic and uncertain environments.