Abstract: As UAV systems become more and more sophisticated in terms of intelligence and autonomy,
it becomes increasingly important to find a common language between human operators and
the automation. Not only should the UAV system make good decisions, its decisions should
also be transparent to the operator. This paper looks at the issue of interfacing UAV operators
with their work domain and explores how principles from cognitive system engineering can be
used to provide a shared representation for the system and its operators. Such a shared
representation should allow natural interaction between multiple autonomous agents and
human actors. They should be able to understand each other’s actions in the context of the
Abstract: Our work addresses the problem of autonomous concept formation from a design point of view, providing an initial answer to the question: What are the design features of an architecture supporting the acquisition of different types of concepts by an autonomous agent?
Autonomous agents, that is systems capable of interacting independently with their environment in the pursuit of their own goals, will provide the framework in which we study the problem of autonomous concept formation. Humans and most animals may in this sense also be regarded as autonomous agents, but our concern will be with artiﬁcial autonomous agents. A detailed survey and discussion of the many issues surrounding the notion of ‘artiﬁcial agency’ is beyond the scope of this thesis and a good overview can be found in [Wooldridge and Jennings, 1995]. Instead we will focus on how artiﬁcial agents could be endowed with representational and modelling capabilities.
The ability to form concepts is an important and recognised cognitive ability, thought to play an essential role in related abilities such as categorisation, language understanding, object identiﬁcation and recognition, reasoning, all of which can be seen as different aspects of intelligence. Concepts and categories are studied within cognitive science, where scientists are concerned with human conceptual abilities and mental representations of categories, but they have been addressed also in the rather different domain of machine learning and classiﬁcatory data analysis, where the focus is on the development of algorithms for clustering problems and induction problems [Mechelen et al., 1993]. The two ﬁelds are well distinct and only recently have started to interact, but even though the importance of concepts have been recognised, the nature of concepts is controversial, in the sense that there is no commonly agreed theory of concepts, and it is still far from obvious which representational means are most suited to capture the many cognitive functions that concepts are involved in.
Among the goals of this thesis there is the attempt to bring together different lines of argumentation that have emerged within philosophy, cognitive science and AI, in order to establish a solid foundation for further research into the representation and acquisition of concepts by autonomous agents. Thus, our results and conclusions will often be stated in terms of new insights and ideas, rather than resulting in new algorithms or formal methods.
Our focus will be on affordance concepts — discussed in detail in Chapter 4 — and our main contributions will be:
* An argument showing that concepts should be thought of as belonging to different kinds, where the differences among these kinds are to be captured in terms of architecture features supporting their acquisition.
* A description (and partial implementation) of a minimal architecture (the Innate Adaptive Behaviour architecture – IAB architecture for short) supporting the acquisition of affordance concepts; the IAB architecture is actually a proposal for a sustaining mechanism, in the sense of [Margolis, 1999], for affordances, and makes clear the necessity of a minimal structure for the representation of affordances.
When addressing concept formation in AI, what can be called the ‘system level’ is often overlooked, which means that concepts and categories are rarely studied from the point of view of a system, autonomous and complete, that might need such constructs and can acquire them only by means of interactions with its environment, under the constraints of its cognitive architecture. Also within psychology, the focus is usually on structural aspects of concepts rather than on developmental issues [Smith and Medin, 1981]. Our approach – an architecture-based approach – is an attempt (i) to show that a system level perspective on concept formation is indeed possible and worth exploring, and (ii) to provide an initial, maybe simple, but concrete example of the insights that can be gained from such an approach. Since the methodology that we propose to study concept formation is a general one, and can be applied also to other types of concepts, we decided to mention broadly ‘autonomous concept formation’ rather than ‘autonomous affordance-concepts formation’ in the title of the thesis.
Abstract: Automation is often accused of adding to the complexity of a system and unnecessarily increasing operator’s workload, and the potential for human error. An approach is needed that guides designers to make the right design choices. CognitiveSystems Engineering (CSE) is a promising approach. However, this field is still young and tangible examples of automation design with an explicit CSE approach do not exist. This paper describes how the design of Total Energy Control System (TECS) that was founded in the late 1970’s can be regarded as an example avant la letter. TECS is an automated flight control system designed to solve many of the issues that classical autopilot and auto-throttle systems have. Since TECS has been designed, implemented, and evaluated it could teach valuable lessons on how Work Domain Analysis (WDA) can guide the design of automated systems as the first phase of CSE approach. The application of WDA to TECS is exemplified using the abstraction hierarchy and the abstraction decomposition space.
Abstract: When we talk about improving Information Systems for Crisis Response and Management, we must consider at least two sorts of problems to solve: the processing of human provided information (perception and knowledge) in combination with other sensor information and the human processing of sensor based information (for situation awareness and decision making). As an illustration, two examples of research work that is done at the D-CIS lab in Delft is presented here. The first example is about Distributed Perception Networks in disaster management and the second example is about cognitive performance factors in decision making (in crisis situations).
Abstract: In actor-agent teams human and artificial entities interact and cooperate in order to enhance and augment their individual and joint cognitive ergonomic and problem solving capabilities. Also actor-agent communities can benefit from ‘ambient cognition’, a novel further reaching concept than ambient intelligence that hardly takes into account the resource limitations and capabilities changing over time of both humans and agents in collaborative settings. The Dutch Companion project aims at the
realization of an agent that takes advantage of the ambient cognition concerning actor-agent system dynamics such that natural emotion-sensitive interaction with an actor over a longer period of time can be sustained. We elaborate on our vision of
pursuing ambient cognition within actor-agent systems and present the plans and expected results of the Dutch Companion project.
Abstract: In actor-agent teams human and artiﬁcial entities interact and cooperate in order to enhance and augment their individual and joint cognitive ergonomic and problem solving capabilities. Also actor-agent communities can beneﬁt from ‘ambient cognition’, a novel further reaching concept than ambient intelligence that hardly takes into account the resource limitations and capabilities changing over time of both humans and agents in collaborative settings. The Dutch Companion project aims at the realization of an agent that takes advantage of the ambient cognition concerning actor-agent system dynamics such that natural social and emotion-sensitive interaction with an actor over a longer period of time can be sustained. We elaborate on our vision of pursuing ambient cognition within actor-agent systems and brieﬂy describe the goals of the Dutch Companion project.
Abstract: Choice of an incorrect representation for the design of automation can dramatically increase
system complexity. Principles from CognitiveSystems Engineering (CSE), which can be used to
identify good representations about the way the ‘world works’, provide a good starting point
for automation design.
This paper discusses, that by choosing the right model for automation design the added
complexity can be limited. But what is the right model for automation? The model of the
environment, or ecology, is preferred above the mental models that human operators have
developed through interacting with the system. The technology has altered the work
environment of the human operator and can have implied to complex or too simplified mental
models. A too complex mental model will bring a too high cognitive load and a simplified
mental model will not be sufficient in all situations. Using the ecology as the basis for the
model of automation, the complexity of the automation is constrained to that of the actual
environment with a minimum share of automation induced complexity.
To illustrate this we considered the design of a conventional autopilot and one based on total
energy control and discuss the mental model pilots have for energy control. Energy control is
the fundamental physics of flight. It is part of the environment thus ecology for pilots and a
proper understanding of energy control helps the pilot to deal with unanticipated event as the
mountain wave condition.
Abstract: This paper illustrates objectives of the DIADEM project which focuses on a
novel combination of advanced technologies which facilitate collaborative information
processing in environmental management applications. The emphasis is on the principles
and tools which facilitate creation of a single information space in advanced systems of
systems through a systematic integration of heterogeneous processes. In particular, we
illustrate the main principles of the DIADEM Process Integration framework, which
supports collaborative processing based on a combination of automated reasoning
processes and cognitive capabilities of multiple human experts, each contributing specific
expertise and processing resources.