Pablo Noriega

Coordination, Organizations, Institutions, and Norms in Agent Systems III

This book constitutes the thoroughly refereed proceedings of the 9th International Workshops on Coordination, Organizations, Institutions and Norms in Agent Systems, COIN 2013. The workshops were co-located with AAMAS 2013, held in St. Paul, MN, USA in May 2013, and with PRIMA 2013, held in Dunedin, New Zealand, in December 2013. The 18 full papers were carefully reviewed and selected from 28 submissions and are presented together with two invited papers. The papers are organized in topical sections such as coordination, organizations, institutions, norms, norm conflict, and norm-aware agents.

Human-inspired model for norm compliance decision making

One of the main goals of the agent community is to provide a trustworthy technology that allows humans to delegate some specific tasks to software agents. Frequently, laws and social norms regulate these tasks. As a consequence agents need mechanisms for reasoning about these norms similarly to the user that has delegated the task to them. Specifically, agents should be able to balance these norms against their internal motivations before taking action. In this paper, we propose a human-inspired model for making decisions about norm compliance based on three different factors: self-interest, enforcement mechanisms and internalized emotions. Different agent personalities can be defined according to the importance given to each factor. These personalities have been experimentally compared and the results are shown in this article.

Reasoning about constitutive norms in BDI agents

Software agents can be members of different institutions along their life; they might even belong to different institutions simultaneously. For these reasons, agents need capabilities that allow them to determine the repercussion that their actions would have within the different institutions. This association between the physical word, in which agents interactions and actions take place, and the institutional world is defined by means of constitutive norms. Currently, the problem of how agents reason about constitutive norms has been tackled from a theoretical perspective only. Thus, there is a lack of more practical proposals that allow the development of software agents capable of reasoning about constitutive norms. In this article we propose an information model, knowledge representation and an inference mechanism to enable Belief-Desire-Intention agents to reason about the consequences of their actions on the institutions and making decisions accordingly. Specifically, the information model, knowledge representation and inference mechanism proposed in this article allows agents to keep track of the institutional state given that they have a physical presence in some real-world environment. Agents have a limited and not fully believable knowledge of the physical world (i.e. they are placed in an uncertain environment). Therefore, our proposal also deals with the uncertainty of the environment.

Reasoning about norms under uncertainty in dynamic environments

The behaviour of norm-autonomous agents is determined by their goals and the norms that are explicitly represented inside their minds. Thus, they require mechanisms for acquiring and accepting norms, determining when norms are relevant to their case, and making decisions about norm compliance. Up until now the existing proposals on norm-autonomous agents assume that agents interact within a deterministic environment that is certainly perceived. In practise, agents interact by means of sensors and actuators under uncertainty with non-deterministic and dynamic environments. Therefore, the existing proposals are unsuitable or, even, useless to be applied when agents have a physical presence in some real-world environment. In response to this problem we have developed the n-BDI architecture. In this paper, we propose a multi-context graded BDI architecture (called n-BDI) that models norm-autonomous agents able to deal with uncertainty in dynamic environments. The n-BDI architecture has been experimentally evaluated and the results are shown in this paper.

Fencing the open fields: empirical concerns on electronic institutions (invited paper)

The regulation of multiagent systems may be approached from different stand-points. In this paper I will take the perspective of using a certain type of devices, electronic institutions, to regulate agent interactions. Furthermore, in this paper I am concerned with the tasks of design and construction of actual electronic institutions and I will explore some of the empirical aspects that one may encounter in such activities. More specifically, I will focus on those empirical aspects that are characteristic of electronic institutions rather than those that may be typical of multi–agent systems development in general or other types of software engineering. I use three examples of actual electronic institutions that show different and complementary features in order to motivate a number of distinctions that may be used to treat empirical features in a systematic way.

Coordination, Organizations, Institutions, and Norms in Agent Systems XI

Norms have been used to represent desirable behaviours that software agents should exhibit in sophisticated multi-agent solutions. An important open research issue refers to group norms, i.e. norms that govern groups of agents. Depending on the interpretation, group norms may be intended to affect the group as a whole, each member of a group, or some members of the group. Moreover, upholding group norms may require coordination among the members of the group. We have identified three sets of agents affected by group norms, namely, (i) the addressees of the norm, (ii) those that will act on it, and (iii) those that are responsible to ensure norm compliance. We present a formalism to represent these, connecting it to a minimalist agent organisation model. We use our formalism to develop a reasoning mechanism which enables agents to identify their position with respect to a group norm, so as to further support agent autonomy and coordination when deciding on possible

Design and evaluation of norm-aware agents based on Normative Markov Decision Processes

In this paper, we show how the impact of norms on the sequential decision making of agents can be formally modeled, computationally determined and quantitatively assessed. For this purpose, we put forward the Normative Markov Decision Process (NMDP) framework - an extension of Markov Decision Processes (MDPs). NMDPs provide an explicit declarative representation of obligation and prohibition as penalties associated to states and conditions on the accessibility of states. Furthermore, NMDPs make an explicit representation of the probability that whoever is responsible for enforcing the norms detects a violation, thus modeling enforcement effectiveness and cost. Then, we approach the problem of reasoning with the NMDP framework by proposing two types of agent: norm-compliant and self-interested. Using these agents, this paper shows how this framework may be employed to study the impact of norms on agent behavior by providing a quantitative measure of the cost of norm abidance and, by the same token, to what extent norms affect reasoning complexity. In particular, we illustrate the use of the NMDP framework through experimental analysis in a simulated environment where the chances of norm violation being detected and penalties are varied. The NMDP framework, an extension of MDPs, for representing the knowledge of norm-aware agents in stochastic environments.Two norm-aware agent models, which use domain-independent standard methods for estimating the rewards of executing plans and using this information to make decisions in complex stochastic environments regulated by norms.Experiments with homogeneous and heterogeneous populations of agents, which allowed us to illustrate how our framework can be used to quantitatively evaluate and compare the agents performance in terms of the variation of parameters of the agents and environment.