The proceedings contain 41 papers. The topics discussed include: falsification of hybrid systems using symbolic reachability and trajectory splicing;inner and outer reachability for the verification of control systems...
ISBN:
(纸本)9781450362825
The proceedings contain 41 papers. The topics discussed include: falsification of hybrid systems using symbolic reachability and trajectory splicing;inner and outer reachability for the verification of control systems;numerical verification of affine systems with up to a billion dimensions;temporal logic robustness for general signal classes;interface-aware signal temporal logic;revisiting timed logics with automata modalities;on the decidability of reachability in linear time-invariant systems;on the decidability of linear bounded periodic cyber-physical systems;characterizations of safety in hybrid inclusions via barrier functions;on topological entropy and stability of switched linear systems;robust invariant sets generation for state-constrained perturbed polynomial systems;a complete characterization of the ordering of path-complete methods;and formal verification of neural network controlled autonomous systems.
We describe four scenario-based implementations of controllers for a player in a simplified R. thoCup-type game. All four implementations are based on the behavioural programming (BP) approach. We first describe a sim...
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ISBN:
(纸本)9781728151250
We describe four scenario-based implementations of controllers for a player in a simplified R. thoCup-type game. All four implementations are based on the behavioural programming (BP) approach. We first describe a simple controller for the player using the state-of-the-art BPjs tool and then show how it can be extended in various ways. The first extension is based on a version of BP where the Z3 SMT solver is used to provide mechanisms for richer composition of modules within the BP model. This allows for modules with higher cohesion and lower coupling. It also allows incrementality: we could use the scenarios we developed for the challenge of MDETOOLS'18 and extend the model to handle the new system. The second extension of BP demonstrated in this paper is a set of idioms for subjecting model components to context. One of the differences between this year's challenge and the challenge we dealt with last year is that following the ball is not the only task that a player needs to handle, there is much more to care for. We demonstrate how we used the idioms for handling context to parametrize scenarios like "go to a target" in a dynamic and natural fashion such that modelers can efficiently specify reusable components similar to the way modern user manuals for advanced products are written. Lastly, in an attempt to make the instructions to the robot even more natural, we demonstrate a third extension based on deep reinforcement learning. Towards substantiating the observation that it is easier to explain things to an intelligent agent than to dumb compiler, we demonstrate how the combination of BP and deep reinforcement learning (DRL) allows for giving abstract instructions to the robot and for teaching it to follow them after a short training session.
The termination and complexity competition (termCOMP) focuses on automated termination and complexity analysis for various kinds of programming paradigms, including categories for term rewriting, integer transition sy...
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ISBN:
(纸本)9783030175023;9783030175016
The termination and complexity competition (termCOMP) focuses on automated termination and complexity analysis for various kinds of programming paradigms, including categories for term rewriting, integer transition systems, imperative programming, logicprogramming, and functional programming. In all categories, the competition also welcomes the participation of tools providing certifiable output. The goal of the competition is to demonstrate the power and advances of the state-of-the-art tools in each of these areas.
The present paper describes briefly a project idea in progress about the evolvement of individuals' opinions, beliefs and perceptions on social networks (such as Facebook, Twitter, Instagram, youtube...) which is ...
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ISBN:
(纸本)9781450389228
The present paper describes briefly a project idea in progress about the evolvement of individuals' opinions, beliefs and perceptions on social networks (such as Facebook, Twitter, Instagram, youtube...) which is a thorny subject that has whetted nowadays the curiosity of a hulk of researchers from various disciplines. For this purpose, differently from a lot of works in the literature, we rely on logical knowledge representation tools in order to investigate the belief merging operation of Artificial Intelligence (AI). The major objective of this project is to provide efficient operator for merging heterogeneous, inconsistent and uncertain multiple sources information in the context of social networks taking into account the fact that opinion can be formed and developed through the concept of social influence with its two forms (informational social influence and normative social influence) and the concept of social trust. We intend thus through this research work presenting an adaptative version to our context of an approach [7] expressed thanks to Answer Set programming (ASP) paradigm with stable model semantics. It is worth to say that our approach profits from the impressive volume data produced by users in social networks about a particular topic by learning from opinions, beliefs and perceptions that their freinds/neighbors share and therefore allows to use this kind of data to extract initial opinions, and to validate the proposed opinions merging process allowing even the prediction of users' behaviors.
The paper investigates fuzzy tolerance relations with membership function valued in a noncommutative residuated lattice. Such tolerance relations appear in the context of the theory of formal concepts. The paper shows...
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ISBN:
(纸本)9781728136028
The paper investigates fuzzy tolerance relations with membership function valued in a noncommutative residuated lattice. Such tolerance relations appear in the context of the theory of formal concepts. The paper shows that given a fuzzy tolerance relation, it is possible to identify a system of attributes and an object-to-attribute relationship, so that the objects are similar to the extent they have common attributes. For this purpose the tolerance classes can be taken as attributes. The paper presents the general description of the structure of fuzzy tolerance classes.
It is well known that (timed) omega-regular properties such as 'p holds at every even position' and 'p occurs at least three times within the next 10 time units' cannot be expressed in Metric Interval ...
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ISBN:
(纸本)9781450362825
It is well known that (timed) omega-regular properties such as 'p holds at every even position' and 'p occurs at least three times within the next 10 time units' cannot be expressed in Metric Interval Temporal logic (MITL) and Event Clock logic (ECL). A standard remedy to this deficiency is to extend these with modalities defined in terms of automata. In this paper, we show that the logics EMITL0,infinity (adding non-deterministic finite automata modalities into the fragment of MITL with only lower- and upper-bound constraints) and EECL (adding automata modalities into ECL) are already as expressive as EMITL (full MITL with automata modalities). In particular, the satisfiability and model-checking problems for EMITL0,8 and EECL are PSPACE-complete, whereas the same problems for EMITL are EXPSPACE-complete. We also provide a simple translation from EMITL0,infinity to diagonal-free timed automata, which enables practical satisfiability and model checking based on off-the-shelf tools.
The recent increase of aging population across Europe and the rest of the globe represents one of the most radical demographic changes in the history of humankind. The increase of ageing society will have a vast impac...
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Several domains in AI need to represent the relational structure as well as model uncertainty. Markov logic is a powerful formalism which achieves this by attaching weights to formulas in finite first-order logic. Tho...
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Several domains in AI need to represent the relational structure as well as model uncertainty. Markov logic is a powerful formalism which achieves this by attaching weights to formulas in finite first-order logic. Though Markov logic Networks (MLNs) have been used for a wide variety of applications, a significant challenge remains that weights do not generalize well when training domain sizes are different from those seen during testing. In particular, it has been observed that marginal probabilities tend to extremes in the limit of increasing domain sizes. As the first contribution of our work, we further characterize the distribution and show that marginal probabilities tend to a constant independent of weights and not always to extremes as was previously observed. As our second contribution, we present a principled solution to this problem by defining Domain-size Aware Markov logic Networks (DA-MLNs) which can be seen as re-parameterizing the MLNs after taking domain size into consideration. For some simple but representative MLN formulas, we formally prove that probabilities defined by DA-MLNs are well behaved. On a practical side, DA-MLNs allow us to generalize the weights learned over small-sized training data to much larger domains. Experiments on three different benchmark MLNs show that our approach results in significant performance gains compared to existing methods.
Driving a car is a complex task,it requires vigilance and experience. When the breaks are applied to a car at the right time and with the right amount of force it can prevent many accidents. A slow moving car or any s...
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ISBN:
(纸本)9781728140018
Driving a car is a complex task,it requires vigilance and experience. When the breaks are applied to a car at the right time and with the right amount of force it can prevent many accidents. A slow moving car or any stationary object on the road is an obstacle for the moving vehicle. It can be avoided by braking/lane change so that the car does not crash. Many factors are involved that effect the braking in cars. Several solutions have been implemented in cars to assist the driver by warning about the incoming obstacle. A device that helps the driver to break automatically is called Automatic Braking system (AUBS). It helps to reduce the accidents due to human error. The AUBS system is designed using a fuzzy logic *** from the obvious inputs such as speed of the car and the distance from the obstacle, several other important factors such as external conditions on road and the tires condition are considered in the proposed approach. The results showed that the Automatic braking system designed showed a reliable and efficient performance.
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