Understanding construction delay analysis and the role of pre-construction programming

Copyright © 2013, American Society of Civil Engineers. This is the author's accepted manuscript. The final published article is available from the link below.Modern construction projects commonly suffer from delay in their completions. The resolution of time and cost claims consequently flowing from such delays continues to remain a difficult undertaking for all project parties. A common approach often relied on by contractors and their employers (or their representatives) to resolve this matter involves applying various delay analysis techniques, which are all based on construction programs originally developed for managing the project. However, evidence from literature suggests that the reliability of these techniques in ensuring successful claims resolution are often undermined by the nature and quality of the underlying program used. As part of a wider research carried out on delay and disruption analysis in practice, this paper reports on an aspect of the study aimed at exploring preconstruction stage programming issues that affect delay claims resolutions. This aspect is based on an in-depth interview with experienced construction planning engineers in the United Kingdom, conducted after an initial large-scale survey on delay and disruption techniques usage. Summary of key findings and conclusions include: (1) most contractors prefer to use linked bar chart format for their baseline programs over conventional critical path method (CPM) networks; (2) baseline programs are developed using planning software packages. Some of these pose difficulties when employed for most delay analysis techniques, except for simpler ones; (3) manpower loading graphs are not commonly developed as part of the main deliverables during preconstruction stage planning. As a result, most programs are not subjected to resource loading and leveling for them to accurately reflect planned resource usage on site. This practice has detrimental effects on the reliability of baseline programs in their use for resolving delay claims; and (4) baseline program development involves many different experts within construction organizations as expected, but with very little involvement of the employer or its representative. Active client involvement is however quite important as it would facilitate quick program approval/acceptance before construction, a necessary requirement for early delay claims settlement, which otherwise are often left unresolved long after the delaying events with the potential of generating into expensive disputes. The study results provide a better understanding of the key issues that need attention if improvements are to be made in delay claim resolutions. Additional research focusing on the testing of these results using a much larger sample and rigorous statistical analysis for generalization purposes would be helpful in advancing the limited knowledge of this subject matter

An Analysis of Service Trading Architectures

Automating the creation and management of SLAs in elec tronic commerce scenarios brings many advantages, such as increasing the speed in the contracting process or allowing providers to deploy an automated provision of services based on those SLAs. We focus on the service trading process, which is the process of locating, selecting, nego tiating, and creating SLAs. This process can be applied to a variety of scenarios and, hence, their requirements are also very different. Despite some service trading architectures have been proposed, currently there is no analysis about which one fits better in each scenario. In this paper, we define a set of properties for abstract service trading architectures based on an analysis of several practical scenarios. Then, we use it to analyse and compare the most relevant abstract architectures for service trad ing. In so doing, the main contribution of this article is a first approach to settle the basis for a qualitative selection of the best architecture for similar trading scenarios

Collaboration in multi-agent system : contract net and beyond

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal

Automated Negotiation for Complex Multi-Agent Resource Allocation

The problem of constructing and analyzing systems of intelligent, autonomous agents is becoming more and more important. These agents may include people, physical robots, virtual humans, software programs acting on behalf of human beings, or sensors. In a large class of multi-agent scenarios, agents may have different capabilities, preferences, objectives, and constraints. Therefore, efficient allocation of resources among multiple agents is often difficult to achieve. Automated negotiation (bargaining) is the most widely used approach for multi-agent resource allocation and it has received increasing attention in the recent years. However, information uncertainty, existence of multiple contracting partners and competitors, agents\u27 incentive to maximize individual utilities, and market dynamics make it difficult to calculate agents\u27 rational equilibrium negotiation strategies and develop successful negotiation agents behaving well in practice. To this end, this thesis is concerned with analyzing agents\u27 rational behavior and developing negotiation strategies for a range of complex negotiation contexts. First, we consider the problem of finding agents\u27 rational strategies in bargaining with incomplete information. We focus on the principal alternating-offers finite horizon bargaining protocol with one-sided uncertainty regarding agents\u27 reserve prices. We provide an algorithm based on the combination of game theoretic analysis and search techniques which finds agents\u27 equilibrium in pure strategies when they exist. Our approach is sound, complete and, in principle, can be applied to other uncertainty settings. Simulation results show that there is at least one pure strategy sequential equilibrium in 99.7% of various scenarios. In addition, agents with equilibrium strategies achieved higher utilities than agents with heuristic strategies. Next, we extend the alternating-offers protocol to handle concurrent negotiations in which each agent has multiple trading opportunities and faces market competition. We provide an algorithm based on backward induction to compute the subgame perfect equilibrium of concurrent negotiation. We observe that agents\u27 bargaining power are affected by the proposing ordering and market competition and for a large subset of the space of the parameters, agents\u27 equilibrium strategies depend on the values of a small number of parameters. We also extend our algorithm to find a pure strategy sequential equilibrium in concurrent negotiations where there is one-sided uncertainty regarding the reserve price of one agent. Third, we present the design and implementation of agents that concurrently negotiate with other entities for acquiring multiple resources. Negotiation agents are designed to adjust 1) the number of tentative agreements and 2) the amount of concession they are willing to make in response to changing market conditions and negotiation situations. In our approach, agents utilize a time-dependent negotiation strategy in which the reserve price of each resource is dynamically determined by 1) the likelihood that negotiation will not be successfully completed, 2) the expected agreement price of the resource, and 3) the expected number of final agreements. The negotiation deadline of each resource is determined by its relative scarcity. Since agents are permitted to decommit from agreements, a buyer may make more than one tentative agreement for each resource and the maximum number of tentative agreements is constrained by the market situation. Experimental results show that our negotiation strategy achieved significantly higher utilities than simpler strategies. Finally, we consider the problem of allocating networked resources in dynamic environment, such as cloud computing platforms, where providers strategically price resources to maximize their utility. While numerous auction-based approaches have been proposed in the literature, our work explores an alternative approach where providers and consumers negotiate resource leasing contracts. We propose a distributed negotiation mechanism where agents negotiate over both a contract price and a decommitment penalty, which allows agents to decommit from contracts at a cost. We compare our approach experimentally, using representative scenarios and workloads, to both combinatorial auctions and the fixed-price model, and show that the negotiation model achieves a higher social welfare

Agents and E-commerce: Beyond Automation

The fast-growing information and communication technologies have shifted the contemporary commerce in both its information and market spaces. Businesses demand a new generation of agile and adaptive commerce systems. Towards this end, software agents, a type of autonomous artifacts, have been viewed as a promising solution. They have been taking an increasingly important part in facilitating e-commerce operations in the last two decades. This article presents a systematized overview of the diversity of agent applications in commerce. The paper argues that agents start playing more substantial role in determining social affairs. They also have a strong potential to be used to build the future highly responsive and smart e-commerce systems. The opportunities and challenges presented by proliferation of agent technologies in e-commerce necessitate the development of insights into their place in information systems research, as well as practical implications for the management

Get It in Writing: Formal Contracts Mitigate Social Dilemmas in Multi-Agent RL

Multi-agent reinforcement learning (MARL) is a powerful tool for training automated systems acting independently in a common environment. However, it can lead to sub-optimal behavior when individual incentives and group incentives diverge. Humans are remarkably capable at solving these social dilemmas. It is an open problem in MARL to replicate such cooperative behaviors in selfish agents. In this work, we draw upon the idea of formal contracting from economics to overcome diverging incentives between agents in MARL. We propose an augmentation to a Markov game where agents voluntarily agree to binding state-dependent transfers of reward, under pre-specified conditions. Our contributions are theoretical and empirical. First, we show that this augmentation makes all subgame-perfect equilibria of all fully observed Markov games exhibit socially optimal behavior, given a sufficiently rich space of contracts. Next, we complement our game-theoretic analysis by showing that state-of-the-art RL algorithms learn socially optimal policies given our augmentation. Our experiments include classic static dilemmas like Stag Hunt, Prisoner's Dilemma and a public goods game, as well as dynamic interactions that simulate traffic, pollution management and common pool resource management.Comment: 12 pages, 8 figures, AAMAS 202

Dispute Settlement in Gatt

This Article describes briefly the way in which the system now operates and the major complaints that have been lodged against it

Reforming U.S. Trade Policy to Protect the Global Environment: A Multilateral Approach

Article published in the Harvard Environmental Law Review

A decommitment strategy in a competitive multi-agent transportation setting

Decommitment is the action of foregoing of a contract for another (superior) offer. It has been shown that, using decommitment, agents can reach higher utility levels in case of negotiations with uncertainty about future prospects. In this paper, we study the decommitment concept for the novel setting of a large-scale logistics setting with multiple, competing companies. Orders for transportation of loads are acquired by agents of the (competing) companies by bidding in online auctions. We find significant increases in profit when the agents can decommit and postpone the transportation of a load to a more suitable time. Furthermore, we analyze the circumstances for which decommitment has a positive impact if agents are capable of handling multiple contracts simultaneously