On the possibility and driving forces of secular stagnation: a general equilibrium analysis applied to Belgium

This paper investigates the possibility of today’s OECD economies entering into a very long period of poor per capita economic growth and very low real interest rates. We construct a general equilibrium model with overlapping generations of heterogeneous individuals, differing in ability and human capital, and with genetic and financial transfers from parents to children. Our model allows to study within one coherent framework the effects of those factors that are most often mentioned in the literature as possible drivers of secular stagnation: demographic change, a slowdown in the rate of technical progress, rising inequality, borrowing constraints, and downward rigidity in the real interest rate. We calibrate our model to Belgium and find that its predictions match key facts in Belgium in 1950-2009 very well. We then simulate projected future changes in technical progress and demography. In alternative scenarios we additionally impose rising inequality, borrowing constraints and/or a lower bound to the real interest rate. When we assume unchanged public policies and a modest future rate of technical progress, our conclusions about future per capita output and growth are rather pessimistic. Demographic change is by far the most influential cause of low growth. If a lower bound to the real interest rate is binding, it could considerably aggravate the problem of stagnation

Time-Lined TCP for the TCP-Friendly Delivery of Streaming Media

This paper introduces Time-lined TCP (TLTCP). TLTCP is a protocol designed to provide TCP-friendly delivery of timesensitive data to applications that are loss-tolerant, such as streaming media players. Previous work on unicast delivery of streaming media over the Internet proposes using UDP and performs congestion control at the user level by regulating the application’s sending rate (attempting to mimic the behavior of TCP in order to be TCP-friendly). TLTCP, on the other hand, is intended to be implemented at the transport level, and is based on TCP with modifications to support time-lines. Instead of treating all data as a byte stream TLTCP allows the application to associate data with deadlines. TLTCP sends data in a similar fashion to TCP until the deadline for a section of data has elapsed; at which point the now obsolete data is discarded in favor of new data. As a result, TLTCP supports TCP-friendly delivery of streaming media by retaining much of TCP’s congestion control functionality. We describe an API for TLTCP that involves augmenting therecvmsg andsendmsg socket calls. We also describe how streaming media applications that use various encoding schemes like MPEG-1 can associate data with deadlines and use TLTCP’s API. We use simulations to examine the behavior of TLTCP under a wide range of networks and workloads. We find that it indeed performs timelined data delivery and under most circumstances bandwidth is shared equally among competing TLTCP and TCP flows. Moreover, those scenarios under which TLTCP appearsto be unfriendly are those under which TCP flows competing only with other TCP flows do not share bandwidth equitably. 1

CROEQS: Contemporaneous Role Ontology-based Expanded Query Search: implementation and evaluation

Searching annotated items in multimedia databases becomes increasingly important. The traditional approach is to build a search engine based on textual metadata. However, in manually annotated multimedia databases, the conceptual level of what is searched for might differ from the high-levelness of the annotations of the items. To address this problem, we present CROEQS, a semantically enhanced search engine. It allows the user to query the annotated persons not only on their name, but also on their roles at the time the multimedia item was broadcast. We also present the ontology used to expand such queries: it allows us to semantically represent the domain knowledge on people fulfilling a role during a temporal interval in general, and politicians holding a political office specifically. The evaluation results show that query expansion using data retrieved from an ontology considerably filters the result set, although there is a performance penalty

Exploring the Benefits of Teams in Multiagent Learning

For problems requiring cooperation, many multiagent systems implement solutions among either individual agents or across an entire population towards a common goal. Multiagent teams are primarily studied when in conflict; however, organizational psychology (OP) highlights the benefits of teams among human populations for learning how to coordinate and cooperate. In this paper, we propose a new model of multiagent teams for reinforcement learning (RL) agents inspired by OP and early work on teams in artificial intelligence. We validate our model using complex social dilemmas that are popular in recent multiagent RL and find that agents divided into teams develop cooperative pro-social policies despite incentives to not cooperate. Furthermore, agents are better able to coordinate and learn emergent roles within their teams and achieve higher rewards compared to when the interests of all agents are aligned.Comment: 10 pages, 6 figures, Published at IJCAI 2022. arXiv admin note: text overlap with arXiv:2204.0747

Towards a Better Understanding of Learning with Multiagent Teams

While it has long been recognized that a team of individual learning agents can be greater than the sum of its parts, recent work has shown that larger teams are not necessarily more effective than smaller ones. In this paper, we study why and under which conditions certain team structures promote effective learning for a population of individual learning agents. We show that, depending on the environment, some team structures help agents learn to specialize into specific roles, resulting in more favorable global results. However, large teams create credit assignment challenges that reduce coordination, leading to large teams performing poorly compared to smaller ones. We support our conclusions with both theoretical analysis and empirical results.Comment: 15 pages, 11 figures, published at the International Joint Conference on Artificial Intelligence (IJCAI) in 202