We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

https://cmi.ac.in/~madhavan/courses/verification-2011/alur-dill-tcs-94.pdf

A theory of timed automata

The 11th edition of Harrison's Principles of Internal Medicine welcomes Anthony Fauci to its editorial staff, in addition to more than 85 new contributors. While the organization of the book is similar to previous editions, major emphasis has been placed on disorders that affect multiple organ systems. Important advances in genetics, immunology, and oncology are emphasized. Many chapters of the book have been rewritten and describe major advances in internal medicine. Subjects that received only a paragraph or two of attention in previous editions are now covered in entire chapters. Among the chapters that have been extensively revised are the chapters on infections in the compromised host, on skin rashes in infections, on many of the viral infections, including cytomegalovirus and Epstein-Barr virus, on sexually transmitted diseases, on diabetes mellitus, on disorders of bone and mineral metabolism, and on lymphadenopathy and splenomegaly. The major revisions in these chapters and many

Harrison's Principles of Internal Medicine

The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents;researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

/pdf/intelligent-agents-theory-and-practice-5dchj7p8pc.pdf

Intelligent Agents: Theory and Practice

/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

Temporal logics are a well investigated formalism for the specification, verification, and synthesis of reactive systems. Within this family, alternating temporal logic, ATL*, has been introduced as a useful generalization of classical linear- and branching-time temporal logics by allowing temporal operators to be indexed by coalitions of agents. Classically, temporal logics are memoryless: once a path in the computation tree is quantified at a given node, the computation that has led to that node is forgotten. Recently, mCTL* has been defined as a memoryful variant of CTL*, where path quantification is memoryful. In the context of multi-agent planning, memoryful quantification enables agents to "relent" and change their goals and strategies depending on their past history. In this paper, we define mATL*, a memoryful extension of ATL*, in which a formula is satisfied at a certain node of a path by taking into account both the future and the past. We study the expressive power of mATL*, its succinctness, as well as related decision problems. We also investigate the relationship between memoryful quantification and past modalities and show their equivalence. We show that both the memoryful and the past extensions come without any computational price; indeed, we prove that both the satisfiability and the model-checking problems are 2EXPTIME-COMPLETE, as they are for ATL*.

/pdf/relentful-strategic-reasoning-in-alternating-time-temporal-3k1jpxvs0e.pdf

Relentful strategic reasoning in alternating-time temporal logic

A schema mapping is a formal specification of the relationship holding between the databases conforming to two given schemas, called source and target, respectively. While in the general case a schema mapping is specified in terms of assertions relating two queries in some given language, various simplified forms of mappings, in particular LAV and GAV, have been considered, based on desirable properties that these forms enjoy. Recent works propose methods for transforming schema mappings to logically equivalent ones of a simplified form. In many cases, this transformation is impossible, and one might be interested in finding simplifications based on a weaker notion, namely logical implication, rather than equivalence. More precisely, given a schema mapping M, find a simplified (LAV, or GAV) schema mapping M' such that M' logically implies M. In this paper we formally introduce this problem, and study it in a variety of cases, providing techniques and complexity bounds. The various cases we consider depend on three parameters: the simplified form to achieve (LAV, or GAV), the type of schema mapping considered (sound, or exact), and the query language used in the schema mapping specification (conjunctive queries and variants over relational databases, or regular path queries and variants over graph databases). Notably, this is the first work on comparing schema mappings for graph databases.

/pdf/simplifying-schema-mappings-1ner4kl9ko.pdf

Simplifying schema mappings

Logic and automata: a match made in heaven

Background Patients with hereditary angioedema with C1 inhibitor deficiency or dysfunction have burdensome recurrent angioedema attacks. The safety, efficacy, and health-related quality of life (HRQoL) outcomes of C1 inhibitor (C1-INH) prophylaxis (intravenously administered) in patients aged 6-11 years were investigated. Methods Eligible patients were enrolled in a randomized, single-blind, crossover, phase 3 trial. After a 12-week baseline observation period (BOP), patients received 500 or 1000 U C1-INH, twice weekly, for 12 weeks before crossing over to the alternate dose for 12 weeks. The primary efficacy end-point was the monthly normalized number of angioedema attacks (NNA). HRQoL was assessed using the EuroQoL 5-dimensional descriptive system youth version and visual analog scale (EQ-VAS). Results Twelve randomized patients had a median (range) age of 10.0 (7-11) years. Mean (SD) percentage reduction in monthly NNA from BOP was 71.1% (27.1%) with 500 U and 84.5% (20.0%) with 1000 U C1-INH. Mean (SD) within-patient difference (-0.4 [0.58]) for monthly NNA with both doses was significant (P = 0.035 [90% CI, -0.706 to -0.102]). Cumulative attack severity, cumulative daily severity, and number of acute attacks treated were reduced. No serious adverse events or discontinuations occurred. Mean EQ-VAS change from BOP to week 9 of treatment (500 U C1-INH, 10.4; 1000 U C1-INH, 21.6) was greater than the minimal important difference, indicating a meaningful HRQoL change. Conclusions C1-INH prophylaxis was effective, safe, and well tolerated in children aged 6-11 years experiencing recurrent angioedema attacks. A post hoc analysis indicated a meaningful improvement in HRQoL with C1-INH. Trial registration ClinicalTrials.gov identifier NCT02052141.

A randomized trial of human C1 inhibitor prophylaxis in children with hereditary angioedema.

Decomposition is a general principle in computational thinking, aiming at decomposing a problem instance into easier subproblems. Indeed, decomposing a transition system into a partitioned transition relation was critical to scaling BDD-based model checking to large state spaces. Since then, it has become a standard technique for dealing with related problems, such as Boolean synthesis. More recently, partitioning has begun to be explored in the synthesis of reactive systems. LTLf synthesis, a finite-horizon version of reactive synthesis with applications in areas such as robotics, seems like a promising candidate for partitioning techniques. After all, the state of the art is based on a BDD-based symbolic algorithm similar to those from model checking, and partitioning could be a potential solution to the current bottleneck of this approach, which is the construction of the state space. In this work, however, we expose fundamental limitations of partitioning that hinder its effective application to symbolic LTLf synthesis. We not only provide evidence for this fact through an extensive experimental evaluation, but also perform an in-depth analysis to identify the reason for these results. We trace the issue to an overall increase in the size of the explored state space, caused by an inability of partitioning to fully exploit state-space minimization, which has a crucial effect on performance. We conclude that more specialized decomposition techniques are needed for LTLf synthesis which take into account the effects of minimization.

/pdf/partitioning-techniques-in-ltlf-synthesis-1q5s3jj28z.pdf

Moshe Y. Vardi

Papers

Relentful strategic reasoning in alternating-time temporal logic

Simplifying schema mappings

Logic and automata: a match made in heaven

A randomized trial of human C1 inhibitor prophylaxis in children with hereditary angioedema.

Partitioning Techniques in LTLf Synthesis.