Abstract. The effects of public announcements, private communications, deceptive messages to groups, and so on, can all be captured by a general mechanism of updating multi-agent models with update action models [3], now in widespread use (see [10] for a textbook treatment). There is a natural extension of the definition of a bisimulation to action models. Surely enough, updating with bisimilar action models gives the same result (modulo bisimulation). But the converse turns out to be false: update models may have the same update effects without being bisimilar. We propose action emulation as a notion of structural equivalence more appropriate for action models, and generalizing standard bisimulation. It is proved that action emulation provides a full characterization of update effect, provided we confine attention to ‘smooth ’ action models. We also give a recipe for turning any action model into a smooth one with the same update effect. Together, this yields a simplification procedure for action models, and it gives designers of multi-agent systems a useful tool for comparing different ways of representing a particular communicative action. 1.

Principal Component Analysis (PCA) is one of the most important methods to handle highdimensional data. However, the high computational complexity makes it hard to apply to the large scale data with high dimensionality, and the used ℓ2-norm makes it sensitive to outliers. A recent work proposed principal component analysis based on ℓ1-norm maximization, which is efficient and robust to outliers. In that work, a greedy strategy was applied due to the difficulty of directly solving the ℓ1-norm maximization problem, which is easy to get stuck in local solution. In this paper, we first propose an efficient optimization algorithm to solve a general ℓ1-norm maximization problem, and then propose a robust principal component analysis with non-greedy ℓ1-norm maximization. Experimental results on real world datasets show that the nongreedy method always obtains much better solution than that of the greedy method. 1

In a pursuit-evasion game, one or more pursuers aim to discover the existence of, and then capture, an evader. The paper studies pursuit-evasion games in which players may have incomplete information concerning the game state. A methodology is presented for the application of a model checker for the logic of knowledge and time to verify epistemic properties in such games. Experimental results are provided from a number of case studies that validate the feasibility of the approach. 1

Abstract Three key ways of updating one’s knowledge are (i) perception of states of affairs, e.g., seeing with one’s own eyes that something is the case, (ii) reception of messages, e.g., being told that something is the case, and (iii) drawing new conclusions from known facts. If one represents knowledge by means of Kripke models, the implicit assumption is that drawing conclusions is immediate. This assumption of logical omniscience is a useful abstraction. It leaves the distinction between (i) and (ii) to be accounted for. In current versions of Update Logic (Dynamic Epistemic Logic, Logic of Communication and Change) perception and message reception are not distinguished. This paper proposes an extension of Update Logic that makes this distinction explicit. The logic deals with three kinds of updates: announcements, changes of the world, and observations about the world in the presence of witnesses. The resulting logic is shown to be complete by means of a reduction to epistemic propositional dynamic logic by a well-known method. 1.1 The Riddle of the Caps ‘I see nobody on the road, ’ said Alice. ‘I only wish I had such eyes, ’ the King remarked in a fretful tone. ‘To be able to see Nobody! And at that distance too!’ Lewis Carroll, Alice in Wonderland. We start with a variation on the so-called ‘wise men puzzle ’ [24]. Imagine four people standing in line, with three of them looking to the left, and one looking to the right. These fellows, let us call them 1,2,3,4, each wear a cap. The leftmost guy,

Abstract We model lying as a communicative act changing the beliefs of the agents in a multi-agent system. With Augustine, we see lying as an utterance believed to be false by the speaker and uttered with the intent to deceive the addressee. The deceit is successful if the lie is believed after the utterance by the addressee. This is our perspective. Also, as common in dynamic epistemic logics, we model the agents addressed by the lie, but we do not (necessarily) model the speaker as one of those agents. This further simplifies the picture: we do not need to model the intention of the speaker, nor do we need to distinguish between knowledge and belief of the speaker: he is the observer of the system and his beliefs are taken to be the truth by the listeners. We provide a sketch of what goes on logically when a lie is communicated. We present a complete logic of manipulative updating, to analyse the effects of lying in public discourse. Next, we turn to the study of lying in games. First, a game-theoretical analysis is used to explain how the possibility of lying makes games such as Liar’s Dice interesting, and how lying is put to use in optimal strategies for playing the game. This is the opposite of the logical manipulative update: instead of always believing the utterance, now, it is never believed. We also give a matching logical analysis for the games perspective, and implement that in the model checker DEMO. Our running example of lying in games is the game of Liar’s Dice.