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Collaborating Authors


Adaptive Intelligent Systems at KSL

AITopics Original Links

We are investigating adaptive intelligent systems -- AI systems that coordinate perception, reasoning and action to pursue multiple goals while functioning autonomously in dynamic environments. After spending many years investigating agents with deep knowledge and powerful reasoning capabilities, our more recent work focuses on more rounded agents that complement their intelligence with human qualities, such as identity, personality, affect, relationship, and embodiment.


Towards Traceability Link Recovery for Self-Adaptive Systems

AAAI Conferences

Self-adaptive systems (SAS) automatically mitigate environmental changes and unexpected system issues at run time by adapting towards optimal configurations that enable continual requirements satisfaction. The increasing proliferation of SASs presents engineering challenges that reflect issues experienced by non-adaptive systems, more specifically, ensuring that continuing assurance for software artifacts is provided. In particular, ensuring that requirements traceability links are appropriately managed at run time in SASs can be an error-prone procedure and may require significant effort from a requirements engineer.  Natural language processing (NLP) techniques have been used to recover broken or missing traceability links efficiently between requirements and other artifacts, however, performing traceability link recovery can introduce significant overhead for SASs.  Specifically, the state-space explosion of possible combinations of environmental states, system parameters, and expressed behaviors can lead to states in which no traceability link exists, thereby necessitating recovery.  This paper proposes Adaptive Requirements Traceability (ART), a conceptual framework for handling traceability recovery in terms of SASs.  We motivate this framework with an illustrative example in the networking domain.


Adaptive infrared-reflecting systems inspired by cephalopods

Science

Materials and systems that statically reflect radiation in the infrared region of the electromagnetic spectrum underpin the performance of many entrenched technologies, including building insulation, energy-conserving windows, spacecraft components, electronics shielding, container packaging, protective clothing, and camouflage platforms. The development of their adaptive variants, in which the infrared-reflecting properties dynamically change in response to external stimuli, has emerged as an important unmet scientific challenge. By drawing inspiration from cephalopod skin, we developed adaptive infrared-reflecting platforms that feature a simple actuation mechanism, low working temperature, tunable spectral range, weak angular dependence, fast response, stability to repeated cycling, amenability to patterning and multiplexing, autonomous operation, robust mechanical properties, and straightforward manufacturability. Our findings may open opportunities for infrared camouflage and other technologies that regulate infrared radiation.


[Policy Forum] Harnessing legal complexity

Science

Complexity science has spread from its origins in the physical sciences into biological and social sciences (1). Increasingly, the social sciences frame policy problems from the financial system to the food system as complex adaptive systems (CAS) and urge policy-makers to design legal solutions with CAS properties in mind. What is often poorly recognized in these initiatives is that legal systems are also complex adaptive systems (2). Just as it seems unwise to pursue regulatory measures while ignoring known CAS properties of the systems targeted for regulation, so too might failure to appreciate CAS qualities of legal systems yield policies founded upon unrealistic assumptions. Despite a long empirical studies tradition in law, there has been little use of complexity science.