Applications Of Partial Polymorphisms In Fine Grained Complexity Of Constraint Satisfaction Problems
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Applications of Partial Polymorphisms in (Fine-Grained) Complexity of Constraint Satisfaction Problems
Author: Biman Roy
language: en
Publisher: Linköping University Electronic Press
Release Date: 2020-03-23
In this thesis we study the worst-case complexity ofconstraint satisfaction problems and some of its variants. We use methods from universal algebra: in particular, algebras of total functions and partial functions that are respectively known as clones and strong partial clones. The constraint satisfactionproblem parameterized by a set of relations ? (CSP(?)) is the following problem: given a set of variables restricted by a set of constraints based on the relations ?, is there an assignment to thevariables that satisfies all constraints? We refer to the set ? as aconstraint language. The inverse CSPproblem over ? (Inv-CSP(?)) asks the opposite: given a relation R, does there exist a CSP(?) instance with R as its set of models? When ? is a Boolean language, then we use the term SAT(?) instead of CSP(?) and Inv-SAT(?) instead of Inv-CSP(?). Fine-grained complexity is an approach in which we zoom inside a complexity class and classify theproblems in it based on their worst-case time complexities. We start by investigating the fine-grained complexity of NP-complete CSP(?) problems. An NP-complete CSP(?) problem is said to be easier than an NP-complete CSP(?) problem if the worst-case time complexity of CSP(?) is not higher thanthe worst-case time complexity of CSP(?). We first analyze the NP-complete SAT problems that are easier than monotone 1-in-3-SAT (which can be represented by SAT(R) for a certain relation R), and find out that there exists a continuum of such problems. For this, we use the connection between constraint languages and strong partial clones and exploit the fact that CSP(?) is easier than CSP(?) when the strong partial clone corresponding to ? contains the strong partial clone of ?. An NP-complete CSP(?) problem is said to be the easiest with respect to a variable domain D if it is easier than any other NP-complete CSP(?) problem of that domain. We show that for every finite domain there exists an easiest NP-complete problem for the ultraconservative CSP(?) problems. An ultraconservative CSP(?) is a special class of CSP problems where the constraint language containsall unary relations. We additionally show that no NP-complete CSP(?) problem can be solved insub-exponential time (i.e. in2^o(n) time where n is the number of variables) given that theexponentialtime hypothesisis true. Moving to classical complexity, we show that for any Boolean constraint language ?, Inv-SAT(?) is either in P or it is coNP-complete. This is a generalization of an earlier dichotomy result, which was only known to be true for ultraconservative constraint languages. We show that Inv-SAT(?) is coNP-complete if and only if the clone corresponding to ? contains essentially unary functions only. For arbitrary finite domains our results are not conclusive, but we manage to prove that theinversek-coloring problem is coNP-complete for each k>2. We exploit weak bases to prove many of theseresults. A weak base of a clone C is a constraint language that corresponds to the largest strong partia clone that contains C. It is known that for many decision problems X(?) that are parameterized bya constraint language ?(such as Inv-SAT), there are strong connections between the complexity of X(?) and weak bases. This fact can be exploited to achieve general complexity results. The Boolean domain is well-suited for this approach since we have a fairly good understanding of Boolean weak bases. In the final result of this thesis, we investigate the relationships between the weak bases in the Boolean domain based on their strong partial clones and completely classify them according to the setinclusion. To avoid a tedious case analysis, we introduce a technique that allows us to discard a largenumber of cases from further investigation.
Empirical Studies in Machine Psychology
Author: Robert Johansson
language: en
Publisher: Linköping University Electronic Press
Release Date: 2024-10-09
This thesis presents Machine Psychology as an interdisciplinary paradigm that integrates learning psychology principles with an adaptive computer system for the development of Artificial General Intelligence (AGI). By synthesizing behavioral psychology with a formal intelligence model, the Non-Axiomatic Reasoning System (NARS), this work explores the potential of operant conditioning paradigms to advance AGI research. The thesis begins by introducing the conceptual foundations of Machine Psychology, detailing its alignment with the theoretical constructs of learning psychology and the formalism of NARS. It then progresses through a series of empirical studies designed to systematically investigate the emergence of increasingly complex cognitive behaviors as NARS interacts with its environment. Initially, operant conditioning is established as a foundational principle for developing adaptive behavior with NARS. Subsequent chapters explore increasingly sophisticated cognitive capabilities, all studied with NARS using experimental paradigms from operant learning psychology: Generalized identity matching, Functional equivalence, and Arbitrarily Applicable Relational Responding. Throughout this research, Machine Psychology is demonstrated to be a promising framework for guiding AGI research, allowing both the manipulation of environmental contingencies and the system’s intrinsic logical processes. The thesis contributes to AGI research by showing how using operant psychological paradigms with NARS can enable cognitive abilities similar to human cognition. These findings set the stage for AGI systems that learn and adapt more like humans, potentially advancing the creation of more general and flexible AI. Denna avhandling introducerar Maskinpsykologi som ett tvärvetenskapligt område där principer från inlärningspsykologi integreras med ett adaptivt datorsystem. Genom att kombinera forskning från beteendepsykologi med en formell modell för intelligens (Non-Axiomatic Reasoning System; NARS), undersöker avhandlingen hur operant betingning kan användas för att driva utvecklingen av Artificiell General Intelligens (AGI) framåt. Avhandlingen börjar med att förklara grunderna i Maskinpsykologi och hur dessa relaterar till både inlärningspsykologi och NARS. Därefter presenteras en serie experiment som systematiskt undersöker hur allt mer komplexa kognitiva beteenden kan uppstå när NARS interagerar med sin omgivning. Till att börja med etableras operant betingning som en central metod för att utveckla adaptiva beteenden med NARS. I de följande kapitlen utforskas hur NARS, genom experiment inspirerade av operant inlärningspsykologi, kan utveckla mer avancerade kognitiva förmågor som till exempel generaliserad identitetsmatchning, funktionell ekvivalens och så kallade arbiträrt applicerbara relationsresponser. Denna forskning visar att Maskinpsykologi är ett lovande verktyg för att vägleda AGI-forskning, eftersom det möjliggör att både påverka omgivningsfaktorer och styra systemets interna logiska processer. Avhandlingen bidrar till AGI-forskning genom att visa hur operanta psykologiska metoder, tillämpade på NARS, kan möjliggöra kognitiva förmågor som liknar mänskligt tänkande. Dessa insikter öppnar nya möjligheter för att utveckla AI-system som kan lära sig och anpassa sig på ett mer mänskligt sätt, vilket kan leda till skapandet av mer generell och flexibel AI.
Designing Human-Swarm Interaction Systems
Author: Oscar Bjurling
language: en
Publisher: Linköping University Electronic Press
Release Date: 2025-02-20
Swarms of Unmanned Aerial Vehicles (UAVs, or drones) are envisioned to transform various fields, from emergency response to law enforcement and military operations. Drone swarms provide scalable, adaptable, and decentralized solutions for dynamic work environments. However, the successful integration of these multi-agent systems into real-world settings presents significant challenges, particularly in terms of how humans can safely and effectively interact with and control these systems. Human-Swarm Interaction (HSI) aims to address these challenges by exploring how human operators can manage multiple drones in a cohesive manner, even under highly complex, uncertain conditions. This thesis studies the problem of designing effective interaction mechanisms and interfaces for human operators to command drone swarms, specifically addressing challenges such as managing a large number of drones, supporting operators’ situational awareness, and balancing between centralized and decentralized control. The research highlights the necessity of rethinking conventional approaches by introducing alternative conceptual models, such as the "choir" metaphor, which re-imagines drone swarms as coordinated, semi-centralized ensembles rather than purely emergent, decentralized collectives. This metaphor aims to balance the collective, often unpredictable behavior of drone swarms with the predictable, directed actions needed in operational environments. By demonstrating how this metaphor can be operationalized in an HSI system architecture, the thesis provides new avenues for conceptualizing human interaction with autonomous systems. Using a design research approach incorporating multiple-case study and scenario-based design activities to envision future swarm application in dialogue with prospective end users, the thesis develops and evaluates prototypes that embody these nuanced HSI concepts. The interface prototypes draw design inspiration from Real-Time Strategy (RTS) games. These elements include group commands, high-level mission planning, and resource pooling to create a hybrid interaction model that allows operators to maintain both a broad overview and precise control of multiple autonomous and collaborating drones. Domain expert evaluations of these prototypes in contexts such as firefighting and airport management validate the practical utility of these concepts. The findings emphasize the value of adopting a Human-Technology-Organization (HTO) perspective in the design of HSI systems. Rather than focusing solely on the interaction between humans and technology, this systems-thinking approach acknowledges that drone swarms must be integrated into larger organizational frameworks, such as emergency response command structures or airport ground operations teams. It demonstrates that successful deployment requires accounting for the broader organizational context, including roles, workflows, and coordination needs. This holistic approach to HSI system design ensures that drone swarms not only meet technical performance criteria, such as reliability, responsiveness, and scalability, but also align with human and organizational needs, facilitating their adoption and effective use in a wide range of real-world scenarios. Ultimately, these contributions are intended to bridge the gap between theoretical models of swarm control and practical deployment, advancing both the field of HSI and the broader adoption of drone swarm technologies. Svärmar av obemannade luftfarkoster (UAV, eller drönare) förväntas omvandla flera områden, exempelvis räddningsinsatser, brottsbekämpning, och militäroperationer. Drönarsvärmar innebar skalbara, anpassningsbara, och decentraliserade lösningar for dynamiska arbetsuppgifter. Den lyckade integreringen av dessa multi-agent-system i verkliga miljöer innebar dock betydande utmaningar, särskilt med avseende på hur människor säkert och effektivt interagerar med och kontrollerar dessa system. Forskningsfältet Människa-Svärm Interaktion (MSI) syftar till att möta dessa utmaningar genom att undersöka hur mänskliga operatorer kan hantera flera drönare på ett sammanhängande vis, även under komplexa och osäkra förhållanden. Denna avhandling utreder problemet att utforma effektiva och säkra interaktionsmekanismer och gränssnitt for mänskliga operatorer att leda drönarsvärmar, specifikt genom att adressera utmaningar som att hantera ett stort antal drönare, stödja operatorers situationsmedvetenhet, och balansera mellan centraliserad och decentraliserad kontroll. Avhandlingen betonar vikten av att ifrågasatta konventionella tillvägagångssätt genom att introducera alternativa konceptuella modeller, såsom "kör"-metaforen, som omtolkar drönarsvärmar som koordinerade, semicentraliserade ensembler snarare än rent decentraliserade kollektiv. Denna metafor syftar till att balansera det kollektiva, ofta oförutsägbara beteendet hos drönarsvärmar med de förutsägbara, riktade handlingar som behövs i operativa miljöer. Genom att visa hur denna metafor kan operationaliseras i en MSI-systemarkitektur, erbjuder avhandlingen nya sätt att konceptualisera mänsklig interaktion med autonoma system. Genom att tillämpa en designforskningsmetod som innefattar fallstudier och scenariobaserade designaktiviteter för att föreställa sig framtida svärmtillämpningar i dialog med potentiella slutanvändare, utvecklar och utvärderar avhandlingen prototyper som manifesterar dessa nyanserade MSI-koncept. Gränssnittens prototyper drar designinspiration från realtidsstrategispel (RTS). Dessa element inkluderar enhetshantering och kommandon på gruppnivå, strategisk uppdragsplanering, och resursdelning för att skapa en hybrid interaktionsmodell som gör det möjligt för operatörer att både bibehålla en bred lägesbild och utöva precis kontroll över flera autonoma och samverkande drönare. Domänexperters utvärderingar av dessa prototyper i arbetskontexter som brandbekämpning och flygplatsledning påvisar den praktiska användbarheten av dessa koncept. Resultaten betonar värdet av att anta ett Människa-Teknik-Organisation (MTO)-perspektiv vid utformningen av MSI-system. Snarare än att enbart fokusera på interaktionen mellan människor och teknik, erkänner detta systemtänkande tillvägagångssätt att drönarsvärmar måste integreras i större organisatoriska ramar, såsom ledningsstrukturer for räddningsinsatser eller markoperativa team på flygplatser. Det visar att framgångsrik implementering av drönarsvärmar kräver att systemutvecklare tar hänsyn till det bredare organisatoriska sammanhanget, inklusive roller, arbetsflöden, och samverkansbehov. Detta holistiska tillvägagångssatt för utformningen av MSI-system säkerställer att drönarsvärmar inte bara uppfyller tekniska prestandakriterier, såsom tillförlitlighet, responsivitet, och skalbarhet, utan också överensstämmer med mänskliga och organisatoriska behov, vilket underlättar deras införande och effektiv användning i en mängd olika tillämpningsscenarier. Över lag är dessa forskningsbidrag avsedda att överbrygga gapet mellan teoretiska modeller för svärmstyrning och praktisk implementering, och därmed avancera och främja både MSI-området och den bredare användningen av svärmteknologier.