C-IPS: Specifying decision interdependencies in negotiations

Abstract. Negotiation is an important mechanism of coordination in multiagent systems. Contrary to early conceptualizations of negotiating agents, we believe that decisions regarding the negotiation issue and the negotiation partner are equally important as the selection of negotiation steps. Our C-IPS approach considers these three aspects as separate decision processes. It requires an explicit specification of interdependencies between them. In this article we address the task of specifying the dynamic interdependencies by means of IPS dynamics. Thereby we introduce a new level of modeling negotiating agents that is above negotiation mechanism and protocol design. IPS dynamics are presented using state charts. We define some generally required states, predicates and actions. We illustrate the dynamics by a simple example. The example is first specified for an idealized scenario and is then extended to a more realistic model that captures some features of open multiagent systems. The well-structured reasoning process for negotiating agents enables more comprehensive and hence more flexible architectures. The explicit modeling of all involved decisions and dependencies eases the understanding, evaluation, and comparison of different approaches to negotiating agents.

Rich Counter-Examples for Temporal-Epistemic Logic Model Checking

Model checking verifies that a model of a system satisfies a given property, and otherwise produces a counter-example explaining the violation. The verified properties are formally expressed in temporal logics. Some temporal logics, such as CTL, are branching: they allow to express facts about the whole computation tree of the model, rather than on each single linear computation. This branching aspect is even more critical when dealing with multi-modal logics, i.e. logics expressing facts about systems with several transition relations. A prominent example is CTLK, a logic that reasons about temporal and epistemic properties of multi-agent systems. In general, model checkers produce linear counter-examples for failed properties, composed of a single computation path of the model. But some branching properties are only poorly and partially explained by a linear counter-example. This paper proposes richer counter-example structures called tree-like annotated counter-examples (TLACEs), for properties in Action-Restricted CTL (ARCTL), an extension of CTL quantifying paths restricted in terms of actions labeling transitions of the model. These counter-examples have a branching structure that supports more complete description of property violations. Elements of these counter-examples are annotated with parts of the property to give a better understanding of their structure. Visualization and browsing of these richer counter-examples become a critical issue, as the number of branches and states can grow exponentially for deeply-nested properties. This paper formally defines the structure of TLACEs, characterizes adequate counter-examples w.r.t. models and failed properties, and gives a generation algorithm for ARCTL properties. It also illustrates the approach with examples in CTLK, using a reduction of CTLK to ARCTL. The proposed approach has been implemented, first by extending the NuSMV model checker to generate and export branching counter-examples, secondly by providing an interactive graphical interface to visualize and browse them.Comment: In Proceedings IWIGP 2012, arXiv:1202.422

Understanding the Relationship between Solar Coronal Abundances and F10.7 cm Radio Emission

Sun-as-a-star coronal plasma composition, derived from full-Sun spectra, and the F10.7 radio flux (2.8 GHz) have been shown to be highly correlated (r = 0.88) during solar cycle 24. However, this correlation becomes nonlinear during increased solar magnetic activity. Here, we use co-temporal, high spatial resolution, multi-wavelength images of the Sun to investigate the underlying causes of the non-linearity between coronal composition (FIP bias) and F10.7 solar index correlation. Using the Karl G. Jansky Very Large Array (JVLA), Hinode/EIS (EUV Imaging Spectrometer), and the Solar Dynamic Observatory (SDO), we observed a small active region, AR 12759, throughout the solar atmosphere from the photosphere to the corona. Results of this study show that the magnetic field strength (flux density) in active regions plays an important role in the variability of coronal abundances, and it is likely the main contributing factor to this non-linearity during increased solar activity. Coronal abundances above cool sunspots are lower than in dispersed magnetic plage regions. Strong magnetic concentrations are associated with stronger F10.7 cm gyroresonance emission. Considering that as the solar cycle moves from minimum to maximum, the size of sunspots and their field strength increase with gyroresonance component, the distinctly different tendencies of radio emission and coronal abundances in the vicinity of sunspots is the likely cause of saturation of Sun-as-a-star coronal abundances during solar maximum, while the F10.7 index remains well correlated with the sunspot number and other magnetic field proxies.Comment: 15 pages, 5 figures, 2 tables, accepted for publication in The Astrophysical Journa

Competence Checking for the Global E-Service Society Using Games

We study the problem of checking the competence of communicative agents operating in a global society in order to receive and offer electronic services. Such a society will be composed of local sub-societies that will often be semi-open, viz., entrance of agents in a semi-open society is conditional to specific admission criteria. Assuming that a candidate agent provides an abstract description of their communicative skills, we present a test that a controller agent could perform in order to decide if a candidate agent should be admitted. We formulate this test by revisiting an existing knowledge representation framework based on games specified as extended logic programs. The resulting framework finds useful application in complex and inter-operable web-services construed as semi-open societies in support of the global vision known as the Semantic Web

Origin of Interface Limitation in Zn O,S CuInS2 Based Solar Cells

Copper indium disulfide CuInS2 grown under Cu rich conditions exhibits high optical quality but suffers predominantly from charge carrier interface recombination, resulting in poor solar cell performance. An unfavorable cliff like conduction band alignment at the buffer CuInS2 interface could be a possible cause of enhanced interface recombination in the device. In this work, we exploit direct and inverse photoelectron spectroscopy together with electrical characterization to investigate the cause of interface recombination in chemical bath deposited Zn O,S co evaporated CuInS2 based devices. Temperature dependent current voltage analyses indeed reveal an activation energy of the dominant charge carrier recombination path, considerably smaller than the absorber bulk band gap, confirming the dominant recombination channel to be present at the Zn O,S CuInS2 interface. However, photoelectron spectroscopy measurements indicate a small 0.1 eV spike like conduction band offset at the Zn O,S CuInS2 interface, excluding an unfavorable energy level alignment to be the prominent cause for strong interface recombination. The observed band bending upon interface formation also suggests Fermi level pinning not to be the main reason, leaving near interface defects as recently observed in Cu rich CuInSe2 as the likely reason for the performance limiting interface recombinatio

Direct Probing of Gap States and Their Passivation in Halide Perovskites by High-Sensitivity, Variable Energy Ultraviolet Photoelectron Spectroscopy

Direct detection of intrinsic defects in halide perovskites (HaPs) by standard methods utilizing optical excitation is quite challenging, due to the low density of defects in most samples of this family of materials (≤10^{15} cm^{–3} in polycrystalline thin films and ≤10^{11} cm^{–3} in single crystals, except melt-grown ones). While several electrical methods can detect defect densities 2 eV) HaPs. By measuring HaP layers on both hole- and electron-contact layers, as well as single crystals without contacts, we conclude that the observed deep defects are intrinsic to the Br-based HaP, and we propose a passivation route via the incorporation of a 2D-forming ligand into the precursor solution

Reports of the AAAI 2019 spring symposium series

Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have already been involved in fatalities, including a pedestrian; and yet machine learning is unable to explain the contexts within which it operates