Don’t miss out on our next seminar of the Logic Lunch series! Next Thursday (April 22nd), Arianna Novaro (ILLC Amsterdam) will talk about Unravelling multi-agent ranked delegations, starting at 12:30. Save the date and join us on Zoom! Please find more information below, and follow us on Twitter and Instagram for more events and activities.
Title: Unravelling multi-agent ranked delegations
Abstract: In this talk, I will present a framework for collective decision-making where the agents have to vote on a given issue, but they can also choose to delegate their vote (if, for instance, they did not have the time or expertise to take a stance on the issue at stake). The agents can express complex delegations, i.e., they can specify a set of trusted delegates and a function–being it a classical voting rule or a propositional formula–to decide their vote, and they can also provide a ranking of preferred delegations. Given these complex delegation ballots, I will present four algorithms that unravel the ballots to get a profile of direct votes, on which the final decision can be taken by using some standard voting rule. In particular, I will discuss both the algorithmic properties and the computational complexity of the four algorithms, for different restrictions on the language of the delegation ballots. This is joint work with Rachael Colley and Umberto Grandi.
We are happy to announce that on April 8th, Mark Law (Imperial College London) will give the fourth talk of our Logic Lunch seminar series, starting at 12:30. Join us on Zoom at this link! And don’t forget to follow us on Twitter and Instagram to keep up to date with our news and events. Please find more information below:
Title: Logic-based Learning of Answer Set Programs
Abstract: In recent years, non-monotonic Inductive Logic Programming (ILP) has received growing interest. Specifically, several new learning frameworks and algorithms have been introduced for learning under the answer set semantics, allowing the learning of common-sense knowledge involving defaults and exceptions, which are essential aspects of human reasoning.
The first part of this seminar will present recent advances which have extended the theory of ILP and yielded a new collection of algorithms, called ILASP (Inductive Learning of Answer Set Programs), which are able to learn ASP programs consisting of normal rules, choice rules and both hard and weak constraints. Learning such programs allows ILASP to be applied in settings which had previously been outside the scope of ILP. In particular, weak constraints represent preference orderings, and so learning weak constraints allows ILASP to be used for preference learning.
The second part of the talk will present more recent work on a less general but much more scalable approach to learning ASP, called FastLAS. FastLAS is able to solve tasks with hypothesis spaces that are many orders of magnitude larger than those tolerated by ILASP, meaning that it can be applied to a greater range of real-world problems.
Last Thursday, Fabrizio Riguzzi from the University of Ferrara gave an excellent talk on Probabilistic Logics in the context of our Logic Lunch Seminar Series. You can watch the entire presentation in the video below:
We are all very looking forward to the first seminar of our Logic Lunch seminar series! Next Thursday at 12:30, Fabrizio Riguzzi from the University of Ferrara will discuss Probabilistic Logics. Save the date and join us on Zoom at this link! You can find more information in the abstract and flyer below and don’t forget to follow us on Twitter and Instagram to keep up to date with our news and events!
Title: Probabilistic Logics
Abstract: This talk will present a point of view over the combination of logic and probability theory. I will first discuss two widely adopted logic languages: logic programming and description logics. After the illustration of similarities and differences, I will present how each has been integrated with probability theory using the so called “distribution semantics”. After a discussion of the semantics, I will briefly survey reasoning algorithms.
We are excited to announce that our Logic Seminars Series will re-start next week every Thursday over lunchtime! If you don’t want to miss out, see the list of our amazing invited speakers below, and don’t forget to save the dates on your calendars!
The last talk for the year within the cycle of online seminars organized by the Milan Logic Group will be given by Vito Michele Abrusci on December 3rd, 2020, at 10:30 via Zoom. Please contact us for details for joining and stay tuned to this website for upcoming news on events for 2021.
Discoveries on syllogisms, induced by linear logic, will be presented:
a) Categorical Propositions and Syllogisms are closed under duality. The system of Aristotelian syllogisms (1st, 2nd and 3rdfigures) is complete under duality.
b) Categorical Propositions and Syllogisms may be represented inside multiplicative fragment of Linear Logic (no need of contraction and weakening rules, no need of first order quantifiers). Better understanding of the Aristotelian notion of “contradictory propositions”.
c) Syllogisms as proof-nets, and thus as geometrical objects and as programs.
d) Why 1st figure syllogisms are simple syllogisms, and the other syllogisms are not simple? A geometrical answer: 1st figure syllogisms are planar proof-nets, whereas other syllogisms are not planar proof-nets.
e) Reductions of syllogisms to 1st figure syllogisms are geometrical ways to transform non-planar graphs into planar graphs.
In this talk, I will discuss logics for social networks, their epistemic extensions, and dynamics in such structure, including diffusion as modeled by threshold models. I will present a selection of recent models for social networks and their epistemics, with a focus on how these may be represented using dynamic term-modal logic (DTML)—a dynamic, quantified modal/epistemic logic, where the subscripts of operators are first-order terms, allowing formulas such as $\exist x K_x N(x,b)$: there exists and agent that knows that it is networked with agent b. DTML is based on an enriched version of action models of dynamic epistemic logic fame, and comes with a complete set of reduction axioms. Modelling social network dynamics in DTML thus directly provide sound and complete logics. Additionally, such logics are decidable when only a finite set of agents is considered.