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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
A Hierarchical Game-Theoretic Decision-Making for Cooperative Multi-Agent Systems Under the Presence of Adversarial Agents
Underlying relationships among Multi-Agent Systems (MAS) in hazardous
scenarios can be represented as Game-theoretic models. This paper proposes a
new hierarchical network-based model called Game-theoretic Utility Tree (GUT),
which decomposes high-level strategies into executable low-level actions for
cooperative MAS decisions. It combines with a new payoff measure based on agent
needs for real-time strategy games. We present an Explore game domain, where we
measure the performance of MAS achieving tasks from the perspective of
balancing the success probability and system costs. We evaluate the GUT
approach against state-of-the-art methods that greedily rely on rewards of the
composite actions. Conclusive results on extensive numerical simulations
indicate that GUT can organize more complex relationships among MAS
cooperation, helping the group achieve challenging tasks with lower costs and
higher winning rates. Furthermore, we demonstrated the applicability of the GUT
using the simulator-hardware testbed - Robotarium. The performances verified
the effectiveness of the GUT in the real robot application and validated that
the GUT could effectively organize MAS cooperation strategies, helping the
group with fewer advantages achieve higher performance.Comment: This paper is accepted by the ACM Symposium on Applied Computing
(SAC) 2023 Technical Track on Intelligent Robotics and Multi-Agent Systems
(IRMAS
A locally active discrete memristor model and its application in a hyperchaotic map
© 2022 Springer Nature Switzerland AG. Part of Springer Nature. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1007/s11071-021-07132-5The continuous memristor is a popular topic of research in recent years, however, there is rare discussion about the discrete memristor model, especially the locally active discrete memristor model. This paper proposes a locally active discrete memristor model for the first time and proves the three fingerprints characteristics of this model according to the definition of generalized memristor. A novel hyperchaotic map is constructed by coupling the discrete memristor with a two-dimensional generalized square map. The dynamical behaviors are analyzed with attractor phase diagram, bifurcation diagram, Lyapunov exponent spectrum, and dynamic behavior distribution diagram. Numerical simulation analysis shows that there is significant improvement in the hyperchaotic area, the quasi-periodic area and the chaotic complexity of the two-dimensional map when applying the locally active discrete memristor. In addition, antimonotonicity and transient chaos behaviors of system are reported. In particular, the coexisting attractors can be observed in this discrete memristive system, resulting from the different initial values of the memristor. Results of theoretical analysis are well verified with hardware experimental measurements. This paper lays a great foundation for future analysis and engineering application of the discrete memristor and relevant the study of other hyperchaotic maps.Peer reviewedFinal Accepted Versio
Functional Representation of the Intentional Bounded Rationality of Decision-Makers: A Laboratory to Study the Decisions a Priori
This work was supported by the Spanish Ministerio de Economia y Competitividad, [ECO2013-48496-C4-3-R and MTM2016-77642-C2-2-P], the Diputacion General de Aragon (DGA) and the European Social Fund [CREVALOR], the Spanish State Research Agency Projects PID2019-10380RBI00/AEI/10.13039/501100011033, and the Andalusian Government Project P20_00673.The judgments of decision-makers are frequently the best way to process the information
on complex alternatives. However, the performances of the alternatives are often not observable in
their entirety, which prevents researchers from conducting controlled empirical studies. This paper
justifies a functional representation that, due to its good predictive results, has been widely used
ad hoc in studies in different branches of knowledge; it formalizes aspects of the human mental
structure that influence the ability of people to decide and the intentional bounded rationality, and
it subsequently analyzes how the reliability of decision-makers is affected by the difficulty of the
problem and the expertise and beliefs of the decision-maker. The main research objective of this
paper is to derive explicitly a general functional form that represents the behavior of a decision-maker
linked to their way of thinking. This functional form allows a laboratory to be created to study a priori
the performance of human decisions, i.e., the probability of choosing each of the alternatives, once the
returns of the alternatives, the level of expertise, and the initial beliefs of the decision-maker are known
exogenously. This laboratory will allow (1) the evaluation of decision support techniques; (2) the
creation of agent-based models that anticipate group performances due to individual interactions;
and (3) the development of other investigations based on statistical simulations.Spanish Government ECO2013-48496-C4-3-R
MTM2016-77642-C2-2-PGobierno de AragonEuropean Social Fund [CREVALOR]Spanish Government PID2019-10380RBI00/AEI/10.13039/501100011033Andalusian Government Project P20_0067
Towards a non-equilibrium thermodynamic theory of ecosystem assembly and development
Non-equilibrium thermodynamics has had a significant historic influence on the development
of theoretical ecology, even informing the very concept of an ecosystem. Much of this influence
has manifested as proposed extremal principles. These principles hold that systems will tend
to maximise certain thermodynamic quantities, subject to the other constraints they operate
under. A particularly notable extremal principle is the maximum entropy production principle
(MaxEPP); that systems maximise their rate of entropy production. However, these principles
are not robustly based in physical theory, and suffer from treating complex ecosystems in
an extremely coarse manner. To address this gap, this thesis derives a limited but physically
justified extremal principle, as well as carrying out a detailed investigation of the impact of
non-equilibrium thermodynamic constraints on the assembly of microbial communities. The extremal
principle we obtain pertains to the switching between states in simple bistable systems,
with switching paths that generate more entropy being favoured. Our detailed investigation
into microbial communities involved developing a novel thermodynamic microbial community
model, using which we found the rate of ecosystem development to be set by the availability
of free-energy. Further investigation was carried out using this model, demonstrating the way
that trade-offs emerging from fundamental thermodynamic constraints impact the dynamics of
assembling microbial communities. Taken together our results demonstrate that theory can be
developed from non-equilibrium thermodynamics, that is both ecologically relevant and physically
well grounded. We find that broad extremal principles are unlikely to be obtained, absent
significant advances in the field of stochastic thermodynamics, limiting their applicability to
ecology. However, we find that detailed consideration of the non-equilibrium thermodynamic
mechanisms that impact microbial communities can broaden our understanding of their assembly
and functioning.Open Acces
Growth trends and site productivity in boreal forests under management and environmental change: insights from long-term surveys and experiments in Sweden
Under a changing climate, current tree and stand growth information is indispensable to the carbon sink strength of boreal forests. Important questions regarding tree growth are to what extent have management and environmental change influenced it, and how it might respond in the future. In this thesis, results from five studies (Papers I-V) covering growth trends, site productivity, heterogeneity in managed forests and potentials for carbon storage in forests and harvested wood products via differing management strategies are presented. The studies were based on observations from national forest inventories and long-term experiments in Sweden. The annual height growth of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) had increased, especially after the millennium shift, while the basal area growth remains stable during the last 40 years (Papers I-II). A positive response on height growth with increasing temperature was observed. The results generally imply a changing growing condition and stand composition. In Paper III, yield capacity of conifers was analysed and compared with existing functions. The results showed that there is a bias in site productivity estimates and the new functions give better prediction of the yield capacity in Sweden. In Paper IV, the variability in stand composition was modelled as indices of heterogeneity to calibrate the relationship between basal area and leaf area index in managed stands of Norway spruce and Scots pine. The results obtained show that the stand structural heterogeneity effects here are of such a magnitude that they cannot be neglected in the implementation of hybrid growth models, especially those based on light interception and light-use efficiency. In the long-term, the net climate benefits in Swedish forests may be maximized through active forest management with high harvest levels and efficient product utilization, compared to increasing carbon storage in standing forests through land set-asides for nature conservation (Paper V). In conclusion, this thesis offers support for the development of evidence-based policy recommendations for site-adapted and sustainable management of Swedish forests in a changing climate
A guide to designing photocontrol in proteins: methods, strategies and applications
Light is essential for various biochemical processes in all domains of life. In its presence certain proteins inside a cell are excited, which either stimulates or inhibits subsequent cellular processes. The artificial photocontrol of specifically proteins is of growing interest for the investigation of scientific questions on the organismal, cellular and molecular level as well as for the development of medicinal drugs or biocatalytic tools. For the targeted design of photocontrol in proteins, three major methods have been developed over the last decades, which employ either chemical engineering of small-molecule photosensitive effectors (photopharmacology), incorporation of photoactive non-canonical amino acids by genetic code expansion (photoxenoprotein engineering), or fusion with photoreactive biological modules (hybrid protein optogenetics). This review compares the different methods as well as their strategies and current applications for the light-regulation of proteins and provides background information useful for the implementation of each technique
Foundations for programming and implementing effect handlers
First-class control operators provide programmers with an expressive and efficient
means for manipulating control through reification of the current control state as a first-class object, enabling programmers to implement their own computational effects and
control idioms as shareable libraries. Effect handlers provide a particularly structured
approach to programming with first-class control by naming control reifying operations
and separating from their handling.
This thesis is composed of three strands of work in which I develop operational
foundations for programming and implementing effect handlers as well as exploring
the expressive power of effect handlers.
The first strand develops a fine-grain call-by-value core calculus of a statically
typed programming language with a structural notion of effect types, as opposed to the
nominal notion of effect types that dominates the literature. With the structural approach,
effects need not be declared before use. The usual safety properties of statically typed
programming are retained by making crucial use of row polymorphism to build and
track effect signatures. The calculus features three forms of handlers: deep, shallow,
and parameterised. They each offer a different approach to manipulate the control state
of programs. Traditional deep handlers are defined by folds over computation trees,
and are the original con-struct proposed by Plotkin and Pretnar. Shallow handlers are
defined by case splits (rather than folds) over computation trees. Parameterised handlers
are deep handlers extended with a state value that is threaded through the folds over
computation trees. To demonstrate the usefulness of effects and handlers as a practical
programming abstraction I implement the essence of a small UNIX-style operating
system complete with multi-user environment, time-sharing, and file I/O.
The second strand studies continuation passing style (CPS) and abstract machine
semantics, which are foundational techniques that admit a unified basis for implementing deep, shallow, and parameterised effect handlers in the same environment. The
CPS translation is obtained through a series of refinements of a basic first-order CPS
translation for a fine-grain call-by-value language into an untyped language. Each refinement moves toward a more intensional representation of continuations eventually
arriving at the notion of generalised continuation, which admit simultaneous support for
deep, shallow, and parameterised handlers. The initial refinement adds support for deep
handlers by representing stacks of continuations and handlers as a curried sequence of
arguments. The image of the resulting translation is not properly tail-recursive, meaning some function application terms do not appear in tail position. To rectify this the
CPS translation is refined once more to obtain an uncurried representation of stacks
of continuations and handlers. Finally, the translation is made higher-order in order to
contract administrative redexes at translation time. The generalised continuation representation is used to construct an abstract machine that provide simultaneous support for
deep, shallow, and parameterised effect handlers. kinds of effect handlers.
The third strand explores the expressiveness of effect handlers. First, I show that
deep, shallow, and parameterised notions of handlers are interdefinable by way of typed
macro-expressiveness, which provides a syntactic notion of expressiveness that affirms
the existence of encodings between handlers, but it provides no information about the
computational content of the encodings. Second, using the semantic notion of expressiveness I show that for a class of programs a programming language with first-class
control (e.g. effect handlers) admits asymptotically faster implementations than possible in a language without first-class control
Digital asset management via distributed ledgers
Distributed ledgers rose to prominence with the advent of Bitcoin, the first provably secure protocol to solve consensus in an open-participation setting. Following, active research and engineering efforts have proposed a multitude of applications and alternative designs, the most prominent being Proof-of-Stake (PoS). This thesis expands the scope of secure and efficient asset management over a distributed ledger around three axes: i) cryptography; ii) distributed systems; iii) game theory and economics. First, we analyze the security of various wallets. We start with a formal model of hardware wallets, followed by an analytical framework of PoS wallets, each outlining the unique properties of Proof-of-Work (PoW) and PoS respectively. The latter also provides a rigorous design to form collaborative participating entities, called stake pools. We then propose Conclave, a stake pool design which enables a group of parties to participate in a PoS system in a collaborative manner, without a central operator. Second, we focus on efficiency. Decentralized systems are aimed at thousands of users across the globe, so a rigorous design for minimizing memory and storage consumption is a prerequisite for scalability. To that end, we frame ledger maintenance as an optimization problem and design a multi-tier framework for designing wallets which ensure that updates increase the ledger’s global state only to a minimal extent, while preserving the security guarantees outlined in the security analysis. Third, we explore incentive-compatibility and analyze blockchain systems from a micro and a macroeconomic perspective. We enrich our cryptographic and systems' results by analyzing the incentives of collective pools and designing a state efficient Bitcoin fee function. We then analyze the Nash dynamics of distributed ledgers, introducing a formal model that evaluates whether rational, utility-maximizing participants are disincentivized from exhibiting undesirable infractions, and highlighting the differences between PoW and PoS-based ledgers, both in a standalone setting and under external parameters, like market price fluctuations. We conclude by introducing a macroeconomic principle, cryptocurrency egalitarianism, and then describing two mechanisms for enabling taxation in blockchain-based currency systems
Synthesis and Characterisation of Low-cost Biopolymeric/mineral Composite Systems and Evaluation of their Potential Application for Heavy Metal Removal
Heavy metal pollution and waste management are two major environmental problems faced in the world today. Anthropogenic sources of heavy metals, especially effluent from industries, are serious environmental and health concerns by polluting surface and ground waters. Similarly, on a global scale, thousands of tonnes of industrial and agricultural waste are discarded into the environment annually. There are several conventional methods to treat industrial effluents, including reverse osmosis, oxidation, filtration, flotation, chemical precipitation, ion exchange resins and adsorption. Among them, adsorption and ion exchange are known to be effective mechanisms for removing heavy metal pollution, especially if low-cost materials can be used.
This thesis was a study into materials that can be used to remove heavy metals from water using low-cost feedstock materials. The synthesis of low-cost composite matrices from agricultural and industrial by-products and low-cost organic and mineral sources was carried out. The feedstock materials being considered include chitosan (generated from industrial seafood waste), coir fibre (an agricultural by-product), spent coffee grounds (a by-product from coffee machines), hydroxyapatite (from bovine bone), and naturally sourced aluminosilicate minerals such as zeolite.
The novel composite adsorbents were prepared using commercially sourced HAp and bovine sourced HAp, with two types of adsorbents being synthesized, including two- and three-component composites. Standard synthetic methods such as precipitation were developed to synthesize these materials, followed by characterization of their structural, physical, and chemical properties (by using FTIR, TGA, SEM, EDX and XRD).
The synthesized materials were then evaluated for their ability to remove metal ions from solutions of heavy metals using single-metal ion type and two-metal ion type solution systems, using the model ion solutions, with quantification of their removal efficiency. It was followed by experimentation using the synthesized adsorbents for metal ion removal in complex systems such as an industrial input stream solution system obtained from a local timber treatment company.
Two-component composites were considered as control composites to compare the removal efficiency of the three-component composites against. The heavy metal removal experiments were conducted under a range of experimental conditions (e.g., pH, sorbent dose, initial metal ion concentration, time of contact). Of the four metal ion systems considered in this study (Cd2+, Pb2+, Cu2+ and Cr as chromate ions), Pb2+ ion removal by the composites was found to be the highest in single-metal and two-metal ion type solution systems, while chromate ion removal was found to be the lowest. The bovine bone-based hydroxyapatite (bHAp) composites were more efficient at removing the metal cations than composites formed from a commercially sourced hydroxyapatite (cHAp).
In industrial input stream solution systems (containing Cu, Cr and As), the Cu2+ ion removal was the highest, which aligned with the observations recorded in the single and two-metal ion type solution systems. Arsenate ion was removed to a higher extent than chromate ion using the three-component composites, while the removal of chromate ion was found to be higher than arsenate ion when using the two-component composites (i.e., the control system).
The project also aimed to elucidate the removal mechanisms of these synthesized composite materials by using appropriate adsorption and kinetic models. The adsorption of metal ions exhibited a range of adsorption behaviours as both the models (Langmuir and Freundlich) were found to fit most of the data recorded in different adsorption systems studied. The pseudo-second-order model was found to be the best fitted to describe the kinetics of heavy metal ion adsorption in all the composite adsorbent systems studied, in single-metal ion type and two-metal ion type solution systems. The ion-exchange mechanism was considered as one of the dominant mechanisms for the removal of cations (in single-metal and two-metal ion type solution systems) and arsenate ions (in industrial input stream solution systems) along with other adsorption mechanisms. In contrast, electrostatic attractions were considered to be the dominant mechanism of removal for chromate ions
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