Erel Segal-Halevi

NegoChat-A: a chat-based negotiation agent with bounded rationality

To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they typically lack the natural language processing support required to enable real-world types of interactions. To address this limitation, we present NegoChat-A, an agent that incorporates several significant research contributions. First, we found that simply modifying existing agents to include an natural language processing module is insufficient to create these agents. Instead, agents that support natural language must have strategies that allow for partial agreements and issue-by-issue interactions. Second, we present NegoChat-A’s negotiation algorithm. This algorithm is based on bounded rationality, and specifically anchoring and aspiration adaptation theory. The agent begins each negotiation interaction by proposing a full offer, which serves as its anchor. Assuming this offer is not accepted, the agent then proceeds to negotiate via partial agreements, proposing the next issue for negotiation based on people’s typical urgency, or order of importance. We present a rigorous evaluation of NegoChat-A, showing its effectiveness in two different negotiation roles.

Waste Makes Haste: Bounded Time Algorithms for Envy-Free Cake Cutting with Free Disposal

We consider the classic problem of envy-free division of a heterogeneous good (“cake”) among several agents. It is known that, when the allotted pieces must be connected, the problem cannot be solved by a finite algorithm for three or more agents. The impossibility result, however, assumes that the entire cake must be allocated. In this article, we replace the entire-allocation requirement with a weaker partial-proportionality requirement: the piece given to each agent must be worth for it at least a certain positive fraction of the entire cake value. We prove that this version of the problem is solvable in bounded time even when the pieces must be connected. We present simple, bounded-time envy-free cake-cutting algorithms for (1) giving each of n agents a connected piece with a positive value; (2) giving each of three agents a connected piece worth at least 1/3; (3) giving each of four agents a connected piece worth at least 1/7; (4) giving each of four agents a disconnected piece worth at least 1/4; and (5) giving each of n agents a disconnected piece worth at least (1 − ε)/n for any positive ε.

SBBA: A Strongly-Budget-Balanced Double-Auction Mechanism

In a seminal paper, McAfee (1992) presented the first dominant strategy truthful mechanism for double auction. His mechanism attains nearly optimal gain-from-trade when the market is sufficiently large. However, his mechanism may leave money on the table, since the price paid by the buyers may be higher than the price paid to the sellers. This money is included in the gain-from-trade and in some cases it accounts for almost all the gain-from-trade, leaving almost no gain-from-trade to the traders. We present SBBA: a variant of McAfee’s mechanism which is strongly budget-balanced. There is a single price, all money is exchanged between buyers and sellers and no money is left on the table. This means that all gain-from-trade is enjoyed by the traders. We generalize this variant to spatially-distributed markets with transit costs.

Monotonicity and Competitive Equilibrium in Cake-cutting

We study the monotonicity properties of solutions in the classic problem of fair cake-cutting – dividing a single heterogeneous resource among agents with subjective utilities. Resource- and population-monotonicity relate to scenarios where the cake, or the number of participants who divide the cake, changes. It is required that the utility of all participants change in the same direction: either all of them are better-off (if there is more to share) or all are worse-off (if there is less to share). We formally introduce these concepts to the cake-cutting setting and present a meticulous axiomatic analysis. We show that classical cake-cutting protocols, like the Cut and Choose, Banach-Knaster, Dubins–Spanier and many other fail to be monotonic. We also show that, when the allotted pieces must be contiguous, proportionality and Pareto-optimality are incompatible with each of the monotonicity axioms. We provide a resource-monotonic protocol for two players and show the existence of rules that satisfy various combinations of contiguousness, proportionality, Pareto-optimality and the two monotonicity axioms.

Demand-flow of agents with gross-substitute valuations

Abstract We consider the gross-substitute (GS) condition introduced by Kelso and Crawford (1982). GS is a condition on the demand-flow in a specific scenario: some items become more expensive while other items retain their price. We prove that GS is equivalent to a much stronger condition, describing the demand-flow in the general scenario in which all prices may change: the demand of GS agents always flows (weakly) downwards, i.e., from items with higher price-increase to items with lower price-increase.

First Steps in Chat-Based Negotiating Agents

To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natural language processing (NLP) methods required to enable real-world types of interactions. In this paper we study how existing agents must be modified to address this limitation. After performing an extensive study of agents’ negotiation with human subjects, we found that simply modifying existing agents to include an NLP module is insufficient to create these agents. Instead the agents’ strategies must be modified to address offers that do not include values for all the discussed issues (as is the case in menu-based interfaces) and consequently issue-by-issue interactions.

Flexible level-1 consensus ensuring stable social choice: analysis and algorithms

Level-1 consensus is a property of a preference profile. Intuitively, it means that there exists some preference relation such that, when ordering the other preference-relations by increasing distance from it, the closer preferences are more frequent in the profile. This is a desirable property, since it enhances the stability of the social choice by guaranteeing that there exists a Condorcet winner and it is elected by all scoring rules. In this paper, we present an algorithm for checking whether a given preference-profile exhibits level-1 consensus. We apply this algorithm to a large number of preference-profiles, both real and randomly-generated, and find that level-1 consensus is very improbable. We back this empirical findings by a simple theoretical proof that, under the impartial culture assumption, the probability of level-1 consensus approaches zero when the number of individuals approaches infinity. Motivated by these observations, we show that the level-1 consensus property can be weakened retaining the stability implications. The weaker level-1 consensus is considerably more probable, both empirically and theoretically. In fact, under the impartial culture assumption, the probability converges to a positive number when the number of individuals approaches infinity.