Background: Value alignment in computer science research is often used to refer to the process of aligning the behaviour of artificial intelligence systems with humans’ desires, but the way the phrase is used often lacks precision. Objectives: In this paper, we conduct a systematic literature review to advance the understanding of value alignment in artificial intelligence by characterising the topic in the context of its research literature. We use this to suggest a more precise definition of the term. Methods: We analyse the abstracts, introductions and conclusions of 172 value alignment research articles that have been published in recent years and synthesise their content using thematic analysis. From these 172 papers we select 85 papers using a structured criteria for a deep analysis, coding these papers in full. Results: Our analysis leads to six themes: value alignment drivers & approaches; challenges in value alignment; values in value alignment; cognitive processes in humans and AI; human-agent teaming; and designing and developing value-aligned systems. Conclusions: By analysing these themes in the context of the literature, we define value alignment as an ongoing process between humans and autonomous agents that aims to express and implement abstract values in diverse contexts, while managing the cognitive limits of both humans and AI agents and also balancing the conflicting ethical and political demands generated by the values in different groups. Our analysis gives rise to a set of research challenges and opportunities in the field of value alignment for future work.

In a normative environment, an agent’s actions are directed not only by its goals but also by the norms activated by its actions and those of other actors. The potential for conflict between agent goals and norms makes decision making challenging, in that it requires looking ahead to consider the longer-term consequences of which goal to satisfy or which norm to comply with in face of conflict. We therefore seek to determine the actions an agent should select at each point in time, taking account of its temporal goals, norms, and their conflicts. We propose a solution in which a normative planning problem is the basis for practical reasoning based on argumentation. Various types of conflict within goals, within norms, and between goals and norms are identified based on temporal properties of these entities. The properties of the best plan(s) with respect to goal achievement and norm compliance are mapped to arguments, followed by mapping their conflicts to attack between arguments, all of which are used to identify why a plan is justified.

Abstract Norms are utilised in agent societies to encourage acceptable behaviour by the participating agents. They can be established or revised from the top-down (authority) or from the bottom-up (populace). The study of norm creation from the bottom-up—or norm emergence/convergence—shows evidence of increasing activity. In consequence, we seek to analyse and categorize the approaches proposed in the literature for facilitating norm emergence. This paper makes three contributions to the study of norm emergence. Firstly, we present the different perspectives of norms and their impact on the norm emergence process, with the aim of comparing their similarities and differences in implementing the norm life cycle. Secondly, we identify the characteristics that support norm emergence that are observed in the emergence literature. Finally, we identify and propose future topics for study for the community, through a discussion of the challenges and opportunities in norm emergence.

Normative capabilities in multi-agent systems (MAS) can be represented within agents, separately as institutions, or a blend of the two. This paper addresses how to extend the principles of open MAS to the provision of normative reasoning capabilities, which are currently either embedded in existing MAS platforms - tightly coupled and inaccessible - or not present. We use a resource-oriented architecture (ROA) pattern, that we call deontic sensors, to make normative reasoning part of an open MAS architecture. The pattern specifies how to loosely couple MAS and normative frameworks, such that each is agnostic of the other, while augmenting the brute facts that an agent perceives with institutional facts, that capture each institution's interpretation of an agent's action. In consequence, a MAS without normative capabilities can acquire them, and an embedded normative framework can be de-coupled and opened to other MAS platforms. More importantly, the deontic sensor pattern allows normative reasoning to be published as services, opening routes to certification and re-use, creation of (formalized) trust and non-specialist access to "on demand'' normative reasoning.

Conflicts between laws can readily arise in situations governed by different laws, a case in point being when the context of an inferior law (or set of regulations) is altered through revision of a superior law. Being able to detect these conflicts automatically and resolve them, for example by proposing revisions to one of the modelled laws or policies, would be highly beneficial for legislators, legal departments of organizations or anybody having to incorporate legal requirements into their own procedures. In this paper we present a model based approach for detecting and finding legal conflicts through a combination of a formal model of legal specifications and a computational model based on answer set programming and inductive logic programming. Given specific scenarios (descriptions of courses of action), our model-based approach can automatically detect whether these scenarios could lead to contradictory outcomes in the different legal specifications. Using these conflicts as use cases, we apply inductive logic programming (ILP) to learn revisions to the legal component that is the source of the conflict. We illustrate our approach using a case-study where a university has to change its studentship programme after the government brings in new immigration regulations.

Acting under several jurisdictions at the same time is becoming the norm rather than the exception, certainly for companies but also (sometimes without knowing) for individuals. In these circumstances disparities among the different laws are inevitable. Here, we present a mathematical and a computational model of interacting legal specifications, along with a mechanism to find conflicts between them. We illustrate the approach by a case study using European Privacy law.

A new scheduler with the capability for distributed quality of service (QoS) provision is presented. Based on the game‐theoretic concepts of coalition formation and bargaining, this scheduler follows a hybrid approach to allocate subcarriers and to satisfy the minimum rate requirement of the wireless users. In the first part of the allocation process, a greedy approach is used to provide users minimum data rate requirements. Then, in the game‐theoretic part of the process, the remaining resources are split in a fair manner between the users by forming dynamically sized coalitions and by allowing users to bargain with each other, using the Nash bargaining solution. The novelty of this approach lies in the fact that it allows the distributed, partly‐cooperative provision of QoS in a multiuser wireless channel. This new scheduler is compared against the proportional fair and greedy schedulers and the simulation results indicate that the proposed scheduler offers better QoS outage performance than others. It also offers fairness and sum rate that are comparable to the PF scheduler, while the comparison with the Greedy scheduler indicates significantly better fairness, but lower sum rate.

In wireless mesh networks (WMN), most routing algorithms apply broadcasting at some stage of the path discovery process. They thereby consume large chunks of the network throughput. Intelligent rebroadcast algorithms aim to reduce this overhead by calculating the usefulness of a rebroadcast and the likelihood of collisions. Unfortunately, this introduces latency and breaks the rebroadcast chain, resulting in reduced reachability. In this paper we present our Social-aware Routing Protocol with Parallel Collision Guidance Broadcasting for WMN (SCG). It reduces rebroadcasting without a loss in reachability and without a significant increase in latency. Our claims are validated through simulations comparing our algorithm with existing protocols.

Abstract While past research in answer-set programming (ASP) mainly focused on theory, ASP solver technology, and applications, the present work situates itself in the context of a quite recent research trend: development support for ASP. In particular, we propose to augment answer-set programs with additional meta-information formulated in a dedicated annotation language, called Lana. This language allows the grouping of rules into coherent blocks and to specify language signatures, types, pre- and postconditions, as well as unit tests for such blocks. While these annotations are invisible to an ASP solver, as they take the form of program comments, they can be interpreted by tools for documentation, testing, and verification purposes, as well as to eliminate sources of common programming errors by realising syntax checking or code completion features. To demonstrate its versatility, we introduce two such tools, viz. (i) ASPDoc, for generating an HTML documentation for a program based on the annotated information, and (ii) ASPUnit, for running and monitoring unit tests on program blocks. Lana is also exploited in the SeaLion system, an integrated development environment for ASP based on Eclipse.

In this paper a distributed, low-complexity, fast and fair resource allocation algorithm for a multiuser, wireless LTE OFDMA channel is proposed. Based on the game theoretic concept of the Nash Bargaining Solution and by grouping users into coalitions of size 2, a cooperative solution to the problem of subcarrier allocation is achieved. The fairness that our algorithm provides matches that offered by the widely accepted Proportional Fair (PF) scheduler. Our simulation results show that the proposed algorithm achieves a sum rate that is almost equivalent (i.e. 90%) to the sum rate achieved by the PF scheduler, while only requiring minimal exchange of information between nodes. At the same time, efficiency enhancements and its distributed nature render it fast and low-complexity enough to be implemented in a real-time wireless system.

In this paper we present a distributed, fast and fair resource allocation algorithm for a multiuser, wireless LTE OFDMA channel. Extending our previous work, we propose additional efficiency enhancements and discuss the protocol issues involved. We further explore the trade-offs between performance and costs and present an analysis of the overhead and time requirements. The proposed algorithm partitions the users of the wireless network into coalitions and, using the game theoretic concept of the Nash Bargaining Solution (NBS), offers a cooperative solution to the subcarrier allocation problem. The use of the NBS ensures that the fairness provided matches that offered by the widely accepted Proportional Fair (PF) scheduler. Simulation results show that the sum rate achieved can be tuned to be almost equivalent to the sum rate of the PF scheduler, while only requiring limited resources and exchange of information between nodes. At the same time, the extensive efficiency enhancements and its distributed nature render the algorithm fast and low-complexity enough to be suitable for implementation in a real-time wireless system.

Abstract Music composition used to be a pen and paper activity. These days music is often composed with the aid of computer software, even to the point where the computer composes parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named Anton , that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes Anton unique in the growing area of algorithmic composition. With near real-time composition, Anton reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an “off-the-shelf” reasoning engine, Anton provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems.

Abstract In this paper we propose a use-case-driven iterative design methodology for normative frameworks, also called virtual institutions, which are used to govern open systems. Our computational model represents the normative framework as a logic program under answer set semantics (ASP). By means of an inductive logic programming approach, implemented using ASP, it is possible to synthesise new rules and revise the existing ones. The learning mechanism is guided by the designer who describes the desired properties of the framework through use cases, comprising (i) event traces that capture possible scenarios, and (ii) a state that describes the desired outcome. The learning process then proposes additional rules, or changes to current rules, to satisfy the constraints expressed in the use cases. Thus, the contribution of this paper is a process for the elaboration and revision of a normative framework by means of a semi-automatic and iterative process driven from specifications of (un)desirable behaviour. The process integrates a novel and general methodology for theory revision based on ASP.

The OTA performance of Frequency Selective Scheduling (WiMAX Band AMC mode) is compared with that of Frequency Diverse Scheduling (WiMAX PUSC mode) as MS velocity is increased for Mobile WiMAX 802.16e. Frequency Selective Scheduling is shown to outperform Frequency Diverse Scheduling for velocities less than 15km/h and demonstrates upto 50% gain in throughput over the latter. The practical implications of this margin are: that pedestrian MSs in urban deployments may leverage the benefits of fast fading for performance gains without risk. And scheduler implementations can benefit from opportunistic switching between the two schemes given appropriate differentiating inputs.

Implementation costs linked to processor memory subsystems (cache miss costs, stalls due to bandwidth limits, etc.) have been shown to be a factor in the performance of a variety of declarative programming tools. This article investigates their impact on answer set solvers and the factors that control them. Experiments independently altering the size and difficulty of input programs allow a qualitative assessment of whether input program or solver design is a greater factor and a quantitative assessment of how much of problem these issues create.A variety of processor performance metrics are recorded and used to provide a detailed picture of what limits solver performance and dispel a number of common misapprehensions.To demonstrate the degree to which these problems can be addressed, smodels-ie is presented. This is a version of the smodels solver with a number of implementation changes to improve cache utilisation, one major aspect of memory costs.

We propose a semantics for disjunctive logic programs, based on the single notion of forcing. We show that the semantics properly extends, in a natural way, previous approaches. A fixpoint characterization is also provided. We also take a closer look at the relationship between disjunctive logic programs and disjunctive‐free logic programs. We present certain criteria under which a disjunctive program is semantically equivalent with its disjunctive‐free (shifted) version.