Probabilistic modeling and reasoning in multiagent decision systems

Ph.DDOCTOR OF PHILOSOPH

Inference in distributed multiagent reasoning systems in cooperation with artificial neural networks

This research is motivated by the need to support inference in intelligent decision support systems offered by multi-agent, distributed intelligent systems involving uncertainty. Probabilistic reasoning with graphical models, known as Bayesian networks (BN) or belief networks, has become an active field of research and practice in artificial intelligence, operations research, and statistics in the last two decades. At present, a BN is used primarily as a stand-alone system. In case of a large problem scope, the large network slows down inference process and is difficult to review or revise. When the problem itself is distributed, domain knowledge and evidence has to be centralized and unified before a single BN can be created for the problem. Alternatively, separate BNs describing related subdomains or different aspects of the same domain may be created, but it is difficult to combine them for problem solving, even if the interdependency relations are available. This issue has been investigated in several works, including most notably Multiply Sectioned BNs (MSBNs) by Xiang [Xiang93]. MSBNs provide a highly modular and efficient framework for uncertain reasoning in multi-agent distributed systems. Inspired by the success of BNs under the centralized and single-agent paradigm, a MSBN representation formalism under the distributed and multi-agent paradigm has been developed. This framework allows the distributed representation of uncertain knowledge on a large and complex environment to be embedded in multiple cooperative agents and effective, exact, and distributed probabilistic inference. What a Bayesian network is, how inference can be done in a Bayesian network under the single-agent paradigm, how multiple agents’ diverse knowledge on a complex environment can be structured as a set of coherent probabilistic graphical models, how these models can be transformed into graphical structures that support message passing, and how message passing can be performed to accomplish tasks in model compilation and distributed inference are covered in details in this thesis

Using causal knowledge to improve retrieval and adaptation in case-based reasoning systems for a dynamic industrial process

Case-based reasoning (CBR) is a reasoning paradigm that starts the reasoning process by examining past similar experiences. The motivation behind this thesis lies in the observation that causal knowledge can guide case-based reasoning in dealing with large and complex systems as it guides humans. In this thesis, case-bases used for reasoning about processes where each case consists of a temporal sequence are considered. In general, these temporal sequences include persistent and transitory (non-persistent) attributes. As these sequences tend to be long, it is unlikely to find a single case in the case-base that closely matches the problem case. By utilizing causal knowledge in the form of a dynamic Bayesian network (DBN) and exploiting the independence implied by the structure of the network and known attributes, this system matches independent portions of the problem case to corresponding sub-cases from the case-base. However, the matching of sub-cases has to take into account the persistence properties of attributes. The approach is then applied to a real life temporal process situation involving an automotive curing oven, in which a vehicle moves through stages within the oven to satisfy some thermodynamic relationships and requirements that change from stage to stage. In addition, testing has been conducted using data randomly generated from known causal networks. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .T54. Source: Masters Abstracts International, Volume: 45-01, page: 0366. Thesis (M.Sc.)--University of Windsor (Canada), 2006

Case studies of Roots, Tubers and Bananas seed systems.

The seed systems of RTB (root, tuber, and banana) crops are unique because they are propagated from vegetative parts of the plant, not from true seed. RTB seed is thus bulkier, more perishable, and more subject to the attacks of pests and diseases than is true seed. Because of this, there is often a gap between potential and real crop yields, which seed interventions seek to narrow. Seed systems are formal or informal networks of people and organizations that produce, plant, and distribute seed. Informal systems may deliver low quality seed, but not always. This book describes 13 RTB seed system interventions, using a framework based on the concepts of seed availability, access, and quality. The 13 case studies included (1) a potato-growers’ association in Ecuador, (2) a hydroponic seed potato in Peru, (3) a yam seed technology in Nigeria, (4) a banana and plantain project in Ghana, (5) a sweetpotato seed project in Tanzania and (6) one in Rwanda, (7) a seed potato system in Kenya, (8) cassava in Nicaragua, (9) seed potato in Malawi, (10) disease-resistant cassava varieties in seven African countries, (11) a tissue culture banana project, (12) an emergency plantain and banana project in East Africa, and (13) a large cassava seed project in six African countries

Radical cognitive science in philosophical psychopathology: the case of depression

The principle purpose of this collection of papers is to explore and apply ideas from various kinds of non-traditional Cognitive Science, as well as comparing them with their more traditional counterparts, in order to reach a better understanding of the symptoms and features of depressive illness. By ‘non-traditional’ I mean to refer to Cognitive Science that makes minimal use of the notion of abstract, post-perceptual, and reconstructive mental representation, is computationally frugal, and treats the mind as fundamentally both embodied and environmentally embedded. This thesis in particular draws on insights from ecological psychology and action-oriented perception, embodied and situated cognition, and predictive processing. After introducing the subject matter, the first substantive paper argues that anhedonia is, in the general case, a disorder determined by disruption to affectively supportive elements of an individual’s environment. The second proposes a predictive-processing approach to explaining the characteristic operation of motivational mental states. This paper supports the third, in which I argue that psychological, somatic, and (action-oriented) perceptual factors all contribute to depressed agents’ struggles and failures to initiate and sustain action. I suggest that these problems should not all be thought of as disorders of motivation per se, but rather as broader kinds of action-oriented cognitive dysfunction. In the fourth paper, I reject Matthew Ratcliffe’s argument for the claim that people with depression are not typically better able to empathise with other people with depression, though I find alternative evidence for this suggestion available to those happy to endorse a more mainstream view of empathy. Finally, I broaden the scope of my investigation to psychopathology in general, and argue that classical (neuro-centric and mechanical) explanations in Psychiatry have inadvertently resulted in psychiatric service users’ subjection to a number of epistemic injustices. This suggests that non-classical theories of psychopathology are not just important for achieving accurate psychiatric explanation, but also for ensuring the ethical treatment of service users

Delay-sensitive Communications Code-Rates, Strategies, and Distributed Control

An ever increasing demand for instant and reliable information on modern communication networks forces codewords to operate in a non-asymptotic regime. To achieve reliability for imperfect channels in this regime, codewords need to be retransmitted from receiver to the transmit buffer, aided by a fast feedback mechanism. Large occupancy of this buffer results in longer communication delays. Therefore, codewords need to be designed carefully to reduce transmit queue-length and thus the delay experienced in this buffer. We first study the consequences of physical layer decisions on the transmit buffer occupancy. We develop an analytical framework to relate physical layer channel to the transmit buffer occupancy. We compute the optimal code-rate for finite-length codewords operating over a correlated channel, under certain communication service guarantees. We show that channel memory has a significant impact on this optimal code-rate. Next, we study the delay in small ad-hoc networks. In particular, we find out what rates can be supported on a small network, when each flow has a certain end-to-end service guarantee. To this end, service guarantee at each intermediate link is characterized. These results are applied to study the potential benefits of setting up a network suitable for network coding in multicast. In particular, we quantify the gains of network coding over classic routing for service provisioned multicast communication over butterfly networks. In the wireless setting, we study the trade-off between communications gains achieved by network coding and the cost to set-up a network enabling network coding. In particular, we show existence of scenarios where one should not attempt to create a network suitable for coding. Insights obtained from these studies are applied to design a distributed rate control algorithm in a large network. This algorithm maximizes sum-utility of all flows, while satisfying per-flow end-to-end service guarantees. We introduce a notion of effective-capacity per communication link that captures the service requirements of flows sharing this link. Each link maintains a price and effective-capacity, and each flow maintains rate and dissatisfaction. Flows and links update their respective variables locally, and we show that their decisions drive the system to an optimal point. We implemented our algorithm on a network simulator and studied its convergence behavior on few networks of practical interest

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

Transformational maintenance by reuse of design histories

This thesis provides theory and procedures for modifying software artifacts implemented by a formal transformation process. Installing modifications requires knowing not only what transformations were applied (a derivation history) to construct the artifact, but also why the application sequence ensures that the artifact meets its specification. The derivation history and the justification are collectively called a design history. A Design Maintenance System (DMS), when provided with a formal change called a maintenance delta, revises a design history to guide construction of a new artifact. A DMS can be used to integrate a stream of deltas into a history, providing implementations as a side effect, leading to an incremental-evolution model for software construction.We provide a broadly applicable formal model of transformation systems in which specifications are performance predicates, subsuming the functional specifications which are traditional for transformation systems. Such performance predicates provide vocabulary used in the design history to describe the effect of applying sets of transformations.A nonprocedural, performance-goal-oriented Transformation Control Language (TCL) is defined to control navigation of the design space for a transformation system. Recording the execution of a TCL metaprogram directly provides a design history.A complete classification of, and representation for, the set of possible maintenance deltas is given in terms of the inputs defined by the transformation system model. Such deltas include not only specification changes, but also changes to implementation support technologies. Delta integration procedures for revising derivation histories given functional or support technology deltas are provided, based on rearranging the order of transformations in the design space. Building on these operations, integration procedures that revise the design history for each type of delta are described. An agenda-oriented TCL execution process dovetails smoothly with the integration procedures.Our DMS is compared to a number of other maintenance systems. By using an explicit delta and verified commutativity, our DMS often reuses transformations correctly when others fail

Computational externalism: The semantic picture of implementation.

The property of being the realization of a computational structure has been argued to be observer-relative. After contrasting the problematic individuation of states in computational systems with the unproblematic individuation of states in dynamical systems, a general diagnosis of the problem is put forward. It is argued that the unwanted proliferation of models for the relation of implementation cannot be blocked unless the labelling scheme is restricted to semantically evaluated items. The instantiation of mathematical dynamical systems, by contrast, is showed to be immune to analogous skeptical arguments due to the virtuous role of measurements in grounding the relevant abstractions. Naturalized semantic properties are proposed to serve as a surrogate for measurements in grounding the relevant abstractions from the physical to the computational level of description, thus making implementations objective. It is argued that a view of implementation that abandons the pervasive internalist view in favor of a view of implementation according to which inputs and outputs are individuated by their broad semantic properties allows us to accept the validity of observer-relativity arguments while preserving the satisfaction of the desiderata of a theory of implementation, as well as the explanatory power of computational- ism as a theory of the mind. The general idea is that of incorporating teleological theories of intentionality within the foundational heart of the notion of computation. An important corollary is that computational properties must be understood as broadly instantiated by relational properties of the implementing system and of its environment. The proposed understanding of implementation is then tested against a number of recalcitrant problems of computationalism. It is argued to be immune to standard objections

Tools and Algorithms for the Construction and Analysis of Systems

This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems